Cumulative Growth of US Manufacturing of 19.1 Percent From May to Oct 2020 at Annual Equivalent 41.8 Percent and Increasing 1.0 Percent in Oct 2020, US Manufacturing 3.9 Percent Lower Than 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, US Manufacturing Underperforming Below Trend in the Lost Economic Cycle of the Global Recession with Economic Growth Underperforming Below Trend Worldwide, Squeeze of Economic Activity by Carry Trades Induced by Zero Interest Rates, United States Inflation, Theory and Reality of Economic History, Cyclical Slow Growth Not Secular Stagnation and Monetary Policy Based on Fear of Deflation, Rules, Discretionary Authorities and Slow Productivity Growth In the Lost Economic Cycle of the Global Recession with Economic Growth Underperforming Below Trend Worldwide, Continuing Recovery of US Economic Indicators, World Cyclical Slow Growth, and Government Intervention in Globalization
Carlos M. Pelaez
© Carlos M. Pelaez, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020.
I United States Industrial Production
IIB Squeeze of Economic Activity by Carry Trades Induced by Zero Interest Rates
IC United States Inflation
IC Long-term US Inflation
ID Current US Inflation
IE Theory and Reality of Economic History, Cyclical Slow Growth Not Secular Stagnation and Monetary Policy Based on Fear of Deflation
II Rules, Discretionary Authorities and Slow Productivity Growth
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
IE Theory and Reality of Economic History, Cyclical Slow Growth Not Secular Stagnation and Monetary Policy Based on Fear of Deflation. Fear of deflation as had occurred during the Great Depression and in Japan was used as an argument for the first round of unconventional monetary policy with 1 percent interest rates from Jun 2003 to Jun 2004 and quantitative easing in the form of withdrawal of supply of 30-year securities by suspension of the auction of 30-year Treasury bonds with the intention of reducing mortgage rates (for fear of deflation see Pelaez and Pelaez, International Financial Architecture (2005), 18-28, and Pelaez and Pelaez, The Global Recession Risk (2007), 83-95). The financial crisis and global recession were caused by interest rate and housing subsidies and affordability policies that encouraged high leverage and risks, low liquidity and unsound credit (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 157-66, Regulation of Banks and Finance (2009b), 217-27, International Financial Architecture (2005), 15-18, The Global Recession Risk (2007), 221-5, Globalization and the State Vol. II (2008b), 197-213, Government Intervention in Globalization (2008c), 182-4). Several past comments of this blog elaborate on these arguments, among which: http://cmpassocregulationblog.blogspot.com/2011/07/causes-of-2007-creditdollar-crisis.html http://cmpassocregulationblog.blogspot.com/2011/01/professor-mckinnons-bubble-economy.html http://cmpassocregulationblog.blogspot.com/2011/01/world-inflation-quantitative-easing.html http://cmpassocregulationblog.blogspot.com/2011/01/treasury-yields-valuation-of-risk.html http://cmpassocregulationblog.blogspot.com/2010/11/quantitative-easing-theory-evidence-and.html http://cmpassocregulationblog.blogspot.com/2010/12/is-fed-printing-money-what-are.html
If the forecast of the central bank is of recession and low inflation with controlled inflationary expectations, monetary policy should consist of lowering the short-term policy rate of the central bank, which in the US is the fed funds rate. The intended effect is to lower the real rate of interest (Svensson 2003LT, 146-7). The real rate of interest, r, is defined as the nominal rate, i, adjusted by expectations of inflation, π*, with all variables defined as proportions: (1+r) = (1+i)/(1+π*) (Fisher 1930). If i, the fed funds rate, is lowered by the Fed, the numerator of the right-hand side is lower such that if inflationary expectations, π*, remain unchanged, the left-hand (1+r) decreases, that is, the real rate of interest, r, declines. Expectations of lowering short-term real rates of interest by policy of the Federal Open Market Committee (FOMC) fixing a lower fed funds rate would lower long-term real rates of interest, inducing with a lag investment and consumption, or aggregate demand, that can lift the economy out of recession. Inflation also increases with a lag by higher aggregate demand and inflation expectations (Fisher 1933). This reasoning explains why the FOMC lowered the fed funds rate in Dec 2008 to 0 to 0.25 percent and left it unchanged.
The fear of the Fed is expected deflation or negative π*. In that case, (1+ π*) < 1, and (1+r) would increase because the right-hand side of the equation would be divided by a fraction. A simple numerical example explains the effect of deflation on the real rate of interest. Suppose that the nominal rate of interest or fed funds rate, i, is 0.25 percent, or in proportion 0.25/100 = 0.0025, such that (1+i) = 1.0025. Assume now that economic agents believe that inflation will remain at 1 percent for a long period, which means that π* = 1 percent, or in proportion 1/100 =0.01. The real rate of interest, using the equation, is (1+0.0025)/(1+0.01) = (1+r) = 0.99257, such that r = 0.99257 - 1 = -0.00743, which is a proportion equivalent to –(0.00743)100 = -0.743 percent. That is, Fed policy has created a negative real rate of interest of 0.743 percent with the objective of inducing aggregate demand by higher investment and consumption. This is true if expected inflation, π*, remains at 1 percent. Suppose now that expectations of deflation become generalized such that π* becomes -1 percent, that is, the public believes prices will fall at the rate of 1 percent in the foreseeable future. Then the real rate of interest becomes (1+0.0025) divided by (1-0.01) equal to (1.0025)/(0.99) = (1+r) = 1.01263, or r = (1.01263-1) = 0.01263, which results in positive real rate of interest of (0.01263)100 = 1.263 percent.
Irving Fisher also identified the impact of deflation on debts as an important cause of deepening contraction of income and employment during the Great Depression illustrated by an actual example (Fisher 1933, 346):
“By March, 1933, liquidation had reduced the debts about 20 percent, but had increased the dollar about 75 percent, so that the real debt, that is the debt measured in terms of commodities, was increased about 40 percent [100%-20%)X(100%+75%) =140%]. Unless some counteracting cause comes along to prevent the fall in the price level, such a depression as that of 1929-1933 (namely when the more the debtors pay the more they owe) tends to continue, going deeper, in a vicious spiral, for many years. There is then no tendency of the boat to stop tipping until it has capsized”
The nominal rate of interest must always be nonnegative, that is, i ≥ 0 (Hicks 1937, 154-5):
“If the costs of holding money can be neglected, it will always be profitable to hold money rather than lend it out, if the rate of interest is not greater than zero. Consequently the rate of interest must always be positive. In an extreme case, the shortest short-term rate may perhaps be nearly zero. But if so, the long-term rate must lie above it, for the long rate has to allow for the risk that the short rate may rise during the currency of the loan, and it should be observed that the short rate can only rise, it cannot fall”
The interpretation by Hicks of the General Theory of Keynes is the special case in which at interest rates close to zero liquidity preference is infinitely or perfectly elastic, that is, the public holds infinitely large cash balances at that near zero interest rate because there is no opportunity cost of foregone interest. Increases in the money supply by the central bank would not decrease interest rates below their near zero level, which is called the liquidity trap. The only alternative public policy would consist of fiscal policy that would act similarly to an increase in investment, increasing employment without raising the interest rate. There are negative nominal interest rates fixed by central banks in Europe and Japan.
An influential view on the policy required to steer the economy away from the liquidity trap is provided by Paul Krugman (1998). Suppose the central bank faces an increase in inflation. An important ingredient of the control of inflation is the central bank communicating to the public that it will maintain a sustained effort by all available policy measures and required doses until inflation is subdued and price stability is attained. If the public believes that the central bank will control inflation only until it declines to a more benign level but not sufficiently low level, current expectations will develop that inflation will be higher once the central bank abandons harsh measures. During deflation and recession the central bank has to convince the public that it will maintain zero interest rates and other required measures until the rate of inflation returns convincingly to a level consistent with expansion of the economy and stable prices. Krugman (1998, 161) summarizes the argument as:
“The ineffectuality of monetary policy in a liquidity trap is really the result of a looking-glass version of the standard credibility problem: monetary policy does not work because the public expects that whatever the central bank may do now, given the chance, it will revert to type and stabilize prices near their current level. If the central bank can credibly promise to be irresponsible—that is, convince the market that it will in fact allow prices to rise sufficiently—it can bootstrap the economy out of the trap”
This view is consistent with results of research by Christina Romer that “the rapid rates of growth of real output in the mid- and late 1930s were largely due to conventional aggregate demand stimulus, primarily in the form of monetary expansion. My calculations suggest that in the absence of these stimuli the economy would have remained depressed far longer and far more deeply than it actually did” (Romer 1992, 757-8, cited in Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 210-2). The average growth rate of the money supply in 1933-1937 was 10 percent per year and increased in the early 1940s. Romer calculates that GDP would have been much lower without this monetary expansion. The growth of “the money supply was primarily due to a gold inflow, which was in turn due to the devaluation in 1933 and to capital flight from Europe because of political instability after 1934” (Romer 1992, 759). Gold inflow coincided with the decline in real interest rates in 1933 that remained negative through the latter part of the 1930s, suggesting that they could have caused increases in spending that was sensitive to declines in interest rates. Bernanke finds dollar devaluation against gold to have been important in preventing further deflation in the 1930s (Bernanke 2002):
“There have been times when exchange rate policy has been an effective weapon against deflation. A striking example from US history is Franklin Roosevelt’s 40 percent devaluation of the dollar against gold in 1933-34, enforced by a program of gold purchases and domestic money creation. The devaluation and the rapid increase in money supply it permitted ended the US deflation remarkably quickly. Indeed, consumer price inflation in the United States, year on year, went from -10.3 percent in 1932 to -5.1 percent in 1933 to 3.4 percent in 1934. The economy grew strongly, and by the way, 1934 was one of the best years of the century for the stock market”
Fed policy is seeking what Irving Fisher proposed “that great depressions are curable and preventable through reflation and stabilization” (Fisher 1933, 350).
The President of the Federal Reserve Bank of Chicago argues that (Charles Evans 2010):
“I believe the US economy is best described as being in a bona fide liquidity trap. Highly plausible projections are 1 percent for core Personal Consumption Expenditures (PCE) inflation at the end of 2012 and 8 percent for the unemployment rate. For me, the Fed’s dual mandate misses are too large to shrug off, and there is currently no policy conflict between improving employment and inflation outcomes”
There are two types of monetary policies that could be used in this situation. First, the Fed could announce a price-level target to be attained within a reasonable time frame (Evans 2010):
“For example, if the slope of the price path is 2 percent and inflation has been underunning the path for some time, monetary policy would strive to catch up to the path. Inflation would be higher than 2 percent for a time until the path was reattained”
Optimum monetary policy with interest rates near zero could consist of “bringing the price level back up to a level even higher than would have prevailed had the disturbance never occurred” (Gauti Eggertsson and Michael Woodford 2003, 207). Bernanke (2003JPY) explains as follows:
“Failure by the central bank to meet its target in a given period leads to expectations of (and public demands for) increased effort in subsequent periods—greater quantities of assets purchased on the open market for example. So even if the central bank is reluctant to provide a time frame for meetings its objective, the structure of the price-level objective provides a means for the bank to commit to increasing its anti-deflationary efforts when its earlier efforts prove unsuccessful. As Eggertsson and Woodford show, the expectations that an increasing price level gap will give rise to intensified effort by the central bank should lead the public to believe that ultimately inflation will replace deflation, a belief that supports the central bank’s own objectives by lowering the current real rate of interest”
Second, the Fed could use its balance sheet to increase purchases of long-term securities together with credible commitment to maintain the policy until the dual mandates of maximum employment and price stability are attained. Policy continues with reinvestment of principal in securities.
In the restatement of the liquidity trap and large-scale policies of monetary/fiscal stimulus, Krugman (1998, 162) finds:
“In the traditional open economy IS-LM model developed by Robert Mundell [1963] and Marcus Fleming [1962], and also in large-scale econometric models, monetary expansion unambiguously leads to currency depreciation. But there are two offsetting effects on the current account balance. On one side, the currency depreciation tends to increase net exports; on the other side, the expansion of the domestic economy tends to increase imports. For what it is worth, policy experiments on such models seem to suggest that these effects very nearly cancel each other out.
Krugman (1998) uses a different dynamic model with expectations that leads to similar conclusions.
The central bank could also be pursuing competitive devaluation of the national currency in the belief that it could increase inflation to a higher level and promote domestic growth and employment at the expense of growth and unemployment in the rest of the world. An essay by Chairman Bernanke in 1999 on Japanese monetary policy received attention in the press, stating that (Bernanke 2000, 165):
“Roosevelt’s specific policy actions were, I think, less important than his willingness to be aggressive and experiment—in short, to do whatever it took to get the country moving again. Many of his policies did not work as intended, but in the end FDR deserves great credit for having the courage to abandon failed paradigms and to do what needed to be done”
Quantitative easing has never been proposed by Chairman Bernanke or other economists as certain science without adverse effects. What has not been mentioned in the press is another suggestion to the Bank of Japan (BOJ) by Chairman Bernanke in the same essay that is very relevant to current events and the contentious issue of ongoing devaluation wars (Bernanke 2000, 161):
“Because the BOJ has a legal mandate to pursue price stability, it certainly could make a good argument that, with interest rates at zero, depreciation of the yen is the best available tool for achieving its mandated objective. The economic validity of the beggar-thy-neighbor thesis is doubtful, as depreciation creates trade—by raising home country income—as well as diverting it. Perhaps not all those who cite the beggar-thy-neighbor thesis are aware that it had its origins in the Great Depression, when it was used as an argument against the very devaluations that ultimately proved crucial to world economic recovery. A yen trading at 100 to the dollar is in no one’s interest”
Chairman Bernanke is referring to the argument by Joan Robinson based on the experience of the Great Depression that: “in times of general unemployment a game of beggar-my-neighbour is played between the nations, each one endeavouring to throw a larger share of the burden upon the others” (Robinson 1947, 156). Devaluation is one of the tools used in these policies (Robinson 1947, 157). Banking crises dominated the experience of the United States, but countries that recovered were those devaluing early such that competitive devaluations rescued many countries from a recession as strong as that in the US (see references to Ehsan Choudhri, Levis Kochin and Barry Eichengreen in Pelaez and Pelaez, Regulation of Banks and Finance (2009b), 205-9; for the case of Brazil that devalued early in the Great Depression recovering with an increasing trade balance see Pelaez, 1968, 1968b, 1972; Brazil devalued and abandoned the gold standard during crises in the historical period as shown by Pelaez 1976, Pelaez and Suzigan 1981). Beggar-my-neighbor policies did work for individual countries but the criticism of Joan Robinson was that it was not optimal for the world as a whole.
Chairman Bernanke (2013Mar 25) reinterprets devaluation and recovery from the Great Depression:
“The uncoordinated abandonment of the gold standard in the early 1930s gave rise to the idea of "beggar-thy-neighbor" policies. According to this analysis, as put forth by important contemporary economists like Joan Robinson, exchange rate depreciations helped the economy whose currency had weakened by making the country more competitive internationally. Indeed, the decline in the value of the pound after 1931 was associated with a relatively early recovery from the Depression by the United Kingdom, in part because of some rebound in exports. However, according to this view, the gains to the depreciating country were equaled or exceeded by the losses to its trading partners, which became less internationally competitive--hence, ‘beggar thy neighbor.’ Economists still agree that Smoot-Hawley and the ensuing tariff wars were highly counterproductive and contributed to the depth and length of the global Depression. However, modern research on the Depression, beginning with the seminal 1985 paper by Barry Eichengreen and Jeffrey Sachs, has changed our view of the effects of the abandonment of the gold standard. Although it is true that leaving the gold standard and the resulting currency depreciation conferred a temporary competitive advantage in some cases, modern research shows that the primary benefit of leaving gold was that it freed countries to use appropriately expansionary monetary policies. By 1935 or 1936, when essentially all major countries had left the gold standard and exchange rates were market-determined, the net trade effects of the changes in currency values were certainly small. Yet the global economy as a whole was much stronger than it had been in 1931. The reason was that, in shedding the strait jacket of the gold standard, each country became free to use monetary policy in a way that was more commensurate with achieving full employment at home.”
Nurkse (1944) raised concern on the contraction of trade by competitive devaluations during the 1930s. Haberler (1937) dwelled on the issue of flexible exchange rates. Bordo and James (2001) provide perceptive exegesis of the views of Haberler (1937) and Nurkse (1944) together with the evolution of thought by Haberler. Policy coordination among sovereigns may be quite difficult in practice even if there were sufficient knowledge and sound forecasts. Friedman (1953) provided strong case in favor of a system of flexible exchange rates.
Eichengreen and Sachs (1985) argue theoretically with measurements using a two-sector model that it is possible for series of devaluations to improve the welfare of all countries. There were adverse effects of depreciation on other countries but depreciation by many countries could be beneficial for all. The important counterfactual is if depreciations by many countries would have promoted faster recovery from the Great Depression. Depreciation in the model of Eichengreen and Sachs (1985) affected domestic and foreign economies through real wages, profitability, international competitiveness and world interest rates. Depreciation causes increase in the money supply that lowers world interest rates, promoting growth of world output. Lower world interest rates could compensate contraction of output from the shift of demand away from home goods originating in neighbor’s exchange depreciation. Eichengreen and Sachs (1985, 946) conclude:
“This much, however, is clear. We do not present a blanket endorsement of the competitive devaluations of the 1930s. Though it is indisputable that currency depreciation conferred macroeconomic benefits on the initiating country, because of accompanying policies the depreciations of the 1930s had beggar-thy-neighbor effects. Though it is likely that currency depreciation (had it been even more widely adopted) would have worked to the benefit of the world as a whole, the sporadic and uncoordinated approach taken to exchange-rate policy in the 1930s tended, other things being equal, to reduce the magnitude of the benefits.”
There could major difference in the current world economy. The initiating impulse for depreciation originates in zero interest rates on the fed funds rate. The dollar is the world’s reserve currency. Risk aversion intermittently channels capital flight to the safe haven of the dollar and US Treasury securities. In the absence of risk aversion, zero interest rates induce carry trades of short positions in dollars and US debt (borrowing) together with long leveraged exposures in risk financial assets such as stocks, emerging stocks, commodities and high-yield bonds. Without risk aversion, the dollar depreciates against every currency in the world. The dollar depreciated against the euro by 39.3 percent from USD 1.1423/EUR con Jun 26, 2003 to USD 1.5914/EUR on Jun 14, 2008 during unconventional monetary policy before the global recession (Table VI-1). Unconventional monetary policy causes devaluation of the dollar relative to other currencies, which can increases net exports of the US that increase aggregate economic activity (Yellen 2011AS). The country issuing the world’s reserve currency appropriates the advantage from initiating devaluation that in policy intends to generate net exports that increase domestic output.
The Swiss franc rate relative to the euro (CHF/EUR) appreciated 18.7 percent on Jan 15, 2015. The Swiss franc rate relative to the dollar (CHF/USD) appreciated 17.7 percent. Central banks are taking measures in anticipation of the quantitative easing by the European Central Bank. On Jan 22, 2015, the European Central Bank (ECB) decided to implement an “expanded asset purchase program” with combined asset purchases of €60 billion per month “until at least Sep 2016 (https://www.ecb.europa.eu/press/pr/date/2015/html/pr150122_1.en.html). The DAX index of German equities increased 1.3 percent on Jan 22, 2015 and 2.1 percent on Jan 23, 2015. The euro depreciated from EUR 1.1611/USD (EUR 0.8613/USD) on Wed Jan 21, 2015, to EUR 1.1206/USD (EUR 0.8924/USD) on Fri Jan 23, 2015, or 3.6 percent. Yellen (2011AS, 6) admits that Fed monetary policy results in dollar devaluation with the objective of increasing net exports, which was the policy that Joan Robinson (1947) labeled as “beggar-my-neighbor” remedies for unemployment. Risk aversion erodes devaluation of the dollar.
Pelaez and Pelaez (Regulation of Banks and Finance (2009b), 208-209) summarize the experience of Brazil as follows:
“During 1927–9, Brazil accumulated ￡30 million of foreign exchange of which ￡20 million were deposited at its stabilization fund (Pelaez 1968, 43–4). After the decline in coffee prices and the first impact of the Great Depression in Brazil a hot money movement wiped out foreign exchange reserves. In addition, capital inflows stopped entirely. The deterioration of the terms of trade further complicated matters, as the value of exports in foreign currency declined abruptly. Because of this exchange crisis, the service of the foreign debt of Brazil became impossible. In August 1931, the federal government was forced to cancel the payment of principal on certain foreign loans. The balance of trade in 1931 was expected to yield ￡20 million whereas the service of the foreign debt alone amounted to ￡22.6 million. Part of the solution given to these problems was typical of the 1930s. In September 1931, the government of Brazil required that all foreign transactions were to be conducted through the Bank of Brazil. This monopoly of foreign exchange was exercised by the Bank of Brazil for the following three years. Export permits were granted only after the exchange derived from sales abroad was officially sold to the Bank, which in turn allocated it in accordance with the needs of the economy. An active black market in foreign exchange developed. Brazil was in the first group of countries that abandoned early the gold standard, in 1931, and suffered comparatively less from the Great Depression. The Brazilian federal government, advised by the BOE, increased taxes and reduced expenditures in 1931 to compensate a decline in custom receipts (Pelaez 1968, 40). Expenditures caused by a revolution in 1932 in the state of Sao Paulo and a drought in the northeast explain the deficit. During 1932–6, the federal government engaged in strong efforts to stabilize the budget. Apart from the deliberate efforts to balance the budget during the 1930s, the recovery in economic activity itself may have induced a large part of the reduction of the deficit (Ibid, 41). Brazil’s experience is similar to that of the United States in that fiscal policy did not promote recovery from the Great Depression.”
Is depreciation of the dollar the best available tool currently for achieving the dual mandate of higher inflation and lower unemployment? Bernanke (2002) finds dollar devaluation against gold to have been important in preventing further deflation in the 1930s (http://www.federalreserve.gov/boarddocs/speeches/2002/20021121/default.htm):
“Although a policy of intervening to affect the exchange value of the dollar is nowhere on the horizon today, it's worth noting that there have been times when exchange rate policy has been an effective weapon against deflation. A striking example from U.S. history is Franklin Roosevelt's 40 percent devaluation of the dollar against gold in 1933-34, enforced by a program of gold purchases and domestic money creation. The devaluation and the rapid increase in money supply it permitted ended the U.S. deflation remarkably quickly. Indeed, consumer price inflation in the United States, year on year, went from -10.3 percent in 1932 to -5.1 percent in 1933 to 3.4 percent in 1934.17 The economy grew strongly, and by the way, 1934 was one of the best years of the century for the stock market. If nothing else, the episode illustrates that monetary actions can have powerful effects on the economy, even when the nominal interest rate is at or near zero, as was the case at the time of Roosevelt's devaluation.”
Should the US devalue following Roosevelt? Alternatively, has monetary policy intended devaluation? Fed policy is seeking, deliberately or as a side effect, what Irving Fisher proposed “that great depressions are curable and preventable through reflation and stabilization” (Fisher, 1933, 350). The Fed has created not only high volatility of assets but also what many countries are regarding as a competitive devaluation similar to those criticized by Nurkse (1944). Yellen (2011AS, 6) admits that Fed monetary policy results in dollar devaluation with the objective of increasing net exports, which was the policy that Joan Robinson (1947) labeled as “beggar-my-neighbor” remedies for unemployment.
Unconventional monetary policy of zero interest rates and large-scale purchases of long-term securities for the balance sheet of the central bank is proposed to prevent deflation. The data of CPI inflation of all goods and CPI inflation excluding food and energy for the past six decades does not show even one negative change, as shown in Table CPIEX.
Table CPIEX, Annual Percentage Changes of the CPI All Items Excluding Food and Energy
Year | Annual ∆% |
1958 | 2.4 |
1959 | 2.0 |
1960 | 1.3 |
1961 | 1.3 |
1962 | 1.3 |
1963 | 1.3 |
1964 | 1.6 |
1965 | 1.2 |
1966 | 2.4 |
1967 | 3.6 |
1968 | 4.6 |
1969 | 5.8 |
1970 | 6.3 |
1971 | 4.7 |
1972 | 3.0 |
1973 | 3.6 |
1974 | 8.3 |
1975 | 9.1 |
1976 | 6.5 |
1977 | 6.3 |
1978 | 7.4 |
1979 | 9.8 |
1980 | 12.4 |
1981 | 10.4 |
1982 | 7.4 |
1983 | 4.0 |
1984 | 5.0 |
1985 | 4.3 |
1986 | 4.0 |
1987 | 4.1 |
1988 | 4.4 |
1989 | 4.5 |
1990 | 5.0 |
1991 | 4.9 |
1992 | 3.7 |
1993 | 3.3 |
1994 | 2.8 |
1995 | 3.0 |
1996 | 2.7 |
1997 | 2.4 |
1998 | 2.3 |
1999 | 2.1 |
2000 | 2.4 |
2001 | 2.6 |
2002 | 2.4 |
2003 | 1.4 |
2004 | 1.8 |
2005 | 2.2 |
2006 | 2.5 |
2007 | 2.3 |
2008 | 2.3 |
2009 | 1.7 |
2010 | 1.0 |
2011 | 1.7 |
2012 | 2.1 |
2013 | 1.8 |
2014 | 1.7 |
2015 | 1.8 |
2016 | 2.2 |
2017 | 1.8 |
2018 | 2.1 |
2019 | 2.2 |
Source: US Bureau of Labor Statistics https://www.bls.gov/cpi/data
The history of producer price inflation in the past five decades does not provide evidence of deflation. The finished core PPI does not register even one single year of decline, as shown in Table PPIEX.
Table PPIEX, Annual Percentage Changes of the PPI Finished Goods Excluding Food and Energy
Year | Annual |
1974 | 11.4 |
1975 | 11.4 |
1976 | 5.7 |
1977 | 6.0 |
1978 | 7.5 |
1979 | 8.9 |
1980 | 11.2 |
1981 | 8.6 |
1982 | 5.7 |
1983 | 3.0 |
1984 | 2.4 |
1985 | 2.5 |
1986 | 2.3 |
1987 | 2.4 |
1988 | 3.3 |
1989 | 4.4 |
1990 | 3.7 |
1991 | 3.6 |
1992 | 2.4 |
1993 | 1.2 |
1994 | 1.0 |
1995 | 2.1 |
1996 | 1.4 |
1997 | 0.3 |
1998 | 0.9 |
1999 | 1.7 |
2000 | 1.3 |
2001 | 1.4 |
2002 | 0.1 |
2003 | 0.2 |
2004 | 1.5 |
2005 | 2.4 |
2006 | 1.5 |
2007 | 1.9 |
2008 | 3.4 |
2009 | 2.6 |
2010 | 1.2 |
2011 | 2.4 |
2012 | 2.6 |
2013 | 1.5 |
2014 | 1.9 |
2015 | 2.0 |
2016 | 1.6 |
2017 | 1.8 |
2018 | 2.3 |
2019 | 2.2 |
Source: US Bureau of Labor Statistics
The producer price index of the US from 1947 to 2020 in Chart I-6 shows various periods of more rapid or less rapid inflation but no bumps. The major event is the decline in 2008 when risk aversion because of the global recession caused the collapse of oil prices from $148/barrel to less than $80/barrel with most other commodity prices also collapsing. The event had nothing in common with explanations of deflation but rather with the concentration of risk exposures in commodities after the decline of stock market indexes. Eventually, there was a flight to government securities because of the fears of insolvency of banks caused by statements supporting proposals for withdrawal of toxic assets from bank balance sheets in the Troubled Asset Relief Program (TARP), as explained by Cochrane and Zingales (2009). The bump in 2008 with decline in 2009 is consistent with the view that zero interest rates with subdued risk aversion induce carry trades into commodity futures.
Chart I-6, US, Producer Price Index, Finished Goods, NSA, 1947-2020
Source: US Bureau of Labor Statistics
Chart I-7 provides 12-month percentage changes of the producer price index from 1948 to 2020. The distinguishing even in Chart I-7 is the Great Inflation of the 1970s. The shape of the two-hump Bactrian camel of the 1970’s resembles the double hump from 2007 to 2020.
Chart I-7, US, Producer Price Index, Finished Goods, 12-Month Percentage Change, NSA, 1948-2020
Source: US Bureau of Labor Statistics
Annual percentage changes of the producer price index from 1948 to 2019 are shown in Table I-1A. The producer price index fell 2.8 percent in 1949 following the adjustment to World War II and fell 0.6 percent in 1952 and 1.0 percent in 1953 around the Korean War. There are two other mild declines of 0.3 percent in 1959 and 0.3 percent in 1963. There are only few subsequent and isolated declines of the producer price index of 1.4 percent in 1986, 0.8 percent in 1998, 1.3 percent in 2002 and 2.6 percent in 2009. The decline of 2009 was caused by unwinding of carry trades in 2008 that had lifted oil prices to $140/barrel during deep global recession because of the panic of probable toxic assets in banks that would be removed with the Troubled Asset Relief Program (TARP) (Cochrane and Zingales 2009). Producer prices fell 3.2 percent in 2015 and declined 1.0 percent in 2016 during collapse of commodity prices form high prices induced by zero interest rates. Producer prices increased 3.2 percent in 2017 and increased 3.1 percent in 2018. Producer prices increased 0.8 percent in 2019. There is no evidence in this history of 66 years of the US producer price index suggesting that there is frequent and persistent deflation shock requiring aggressive unconventional monetary policy. The design of such anti-deflation policy could provoke price and financial instability because of lags in effect of monetary policy, model errors, inaccurate forecasts and misleading analysis of current economic conditions.
Table I-1A, US, Annual PPI Inflation ∆% 1948-2019
Year | Annual |
1948 | 8.0 |
1949 | -2.8 |
1950 | 1.8 |
1951 | 9.2 |
1952 | -0.6 |
1953 | -1.0 |
1954 | 0.3 |
1955 | 0.3 |
1956 | 2.6 |
1957 | 3.8 |
1958 | 2.2 |
1959 | -0.3 |
1960 | 0.9 |
1961 | 0.0 |
1962 | 0.3 |
1963 | -0.3 |
1964 | 0.3 |
1965 | 1.8 |
1966 | 3.2 |
1967 | 1.1 |
1968 | 2.8 |
1969 | 3.8 |
1970 | 3.4 |
1971 | 3.1 |
1972 | 3.2 |
1973 | 9.1 |
1974 | 15.4 |
1975 | 10.6 |
1976 | 4.5 |
1977 | 6.4 |
1978 | 7.9 |
1979 | 11.2 |
1980 | 13.4 |
1981 | 9.2 |
1982 | 4.1 |
1983 | 1.6 |
1984 | 2.1 |
1985 | 1.0 |
1986 | -1.4 |
1987 | 2.1 |
1988 | 2.5 |
1989 | 5.2 |
1990 | 4.9 |
1991 | 2.1 |
1992 | 1.2 |
1993 | 1.2 |
1994 | 0.6 |
1995 | 1.9 |
1996 | 2.7 |
1997 | 0.4 |
1998 | -0.8 |
1999 | 1.8 |
2000 | 3.8 |
2001 | 2.0 |
2002 | -1.3 |
2003 | 3.2 |
2004 | 3.6 |
2005 | 4.8 |
2006 | 3.0 |
2007 | 3.9 |
2008 | 6.3 |
2009 | -2.6 |
2010 | 4.2 |
2011 | 6.1 |
2012 | 1.9 |
2013 | 1.2 |
2014 | 1.9 |
2015 | -3.2 |
2016 | -1.0 |
2017 | 3.2 |
2018 | 3.1 |
2019 | 0.8 |
Source: US Bureau of Labor Statistics
Chart I-12 provides the consumer price index NSA from 1913 to 2020. The dominating characteristic is the increase in slope during the Great Inflation from the middle of the 1960s through the 1970s. There is long-term inflation in the US and no evidence of deflation risks.
Chart I-12, US, Consumer Price Index, NSA, 1913-2020
Source: US Bureau of Labor Statistics https://www.bls.gov/cpi/data.htm
Chart I-13 provides 12-month percentage changes of the consumer price index from 1914 to 2020. The only episode of deflation after 1950 is in 2009, which is explained by the reversal of speculative commodity futures carry trades that were induced by interest rates driven to zero in a shock of monetary policy in 2008. The only persistent case of deflation is from 1930 to 1933, which has little if any relevance to the contemporary United States economy. There are actually three waves of inflation in the second half of the 1960s, in the mid-1970s and again in the late 1970s. Inflation rates then stabilized in a range with only two episodes above 5 percent.
Chart I-13, US, Consumer Price Index, All Items, 12- Month Percentage Change 1914-2020
Source: US Bureau of Labor Statistics https://www.bls.gov/cpi/data.htm
Table I-2 provides annual percentage changes of United States consumer price inflation from 1914 to 2019. There have been only cases of annual declines of the CPI after wars:
- World War I minus 10.5 percent in 1921 and minus 6.1 percent in 1922 following cumulative increases of 83.5 percent in four years from 1917 to 1920 at the average of 16.4 percent per year
- World War II: minus 1.2 percent in 1949 following cumulative 33.9 percent in three years from 1946 to 1948 at average 10.2 percent per year
- Minus 0.4 percent in 1955 two years after the end of the Korean War
- Minus 0.4 percent in 2009.
- The decline of 0.4 percent in 2009 followed increase of 3.8 percent in 2008 and is explained by the reversal of speculative carry trades into commodity futures that were created in 2008 as monetary policy rates were driven to zero. The reversal occurred after misleading statement on toxic assets in banks in the proposal for TARP (Cochrane and Zingales 2009).
There were declines of 1.7 percent in both 1927 and 1928 during the episode of revival of rules of the gold standard. The only persistent deflationary period since 1914 was during the Great Depression in the years from 1930 to 1933 and again in 1938-1939. Consumer prices increased only 0.1 percent in 2015 because of the collapse of commodity prices from artificially high levels induced by zero interest rates. Consumer prices increased 1.3 percent in 2016, increasing at 2.1 percent in 2017. Consumer prices increased 2.4 percent in 2018, increasing at 1.8 percent in 2019. Fear of deflation based on that experience does not justify unconventional monetary policy of zero interest rates that has failed to stop deflation in Japan. Financial repression causes far more adverse effects on allocation of resources by distorting the calculus of risk/returns than alleged employment-creating effects or there would not be current recovery without jobs and hiring after zero interest rates since Dec 2008 and intended now forever in a self-imposed forecast growth and employment mandate of monetary policy. Unconventional monetary policy drives wide swings in allocations of positions into risk financial assets that generate instability instead of intended pursuit of prosperity without inflation. There is insufficient knowledge and imperfect tools to maintain the gap of actual relative to potential output constantly at zero while restraining inflation in an open interval of (1.99, 2.0). Symmetric targets appear to have been abandoned in favor of a self-imposed single jobs mandate of easing monetary policy even with the economy growing at or close to potential output that is actually a target of growth forecast. The impact on the overall economy and the financial system of errors of policy are magnified by large-scale policy doses of trillions of dollars of quantitative easing and zero interest rates. The US economy has been experiencing financial repression as a result of negative real rates of interest during nearly a decade and programmed in monetary policy statements until 2015 or, for practical purposes, forever. The essential calculus of risk/return in capital budgeting and financial allocations has been distorted. If economic perspectives are doomed until 2015 such as to warrant zero interest rates and open-ended bond-buying by “printing” digital bank reserves (http://cmpassocregulationblog.blogspot.com/2010/12/is-fed-printing-money-what-are.html; see Shultz et al 2012), rational investors and consumers will not invest and consume until just before interest rates are likely to increase. Monetary policy statements on intentions of zero interest rates for another three years or now virtually forever discourage investment and consumption or aggregate demand that can increase economic growth and generate more hiring and opportunities to increase wages and salaries. The doom scenario used to justify monetary policy accentuates adverse expectations on discounted future cash flows of potential economic projects that can revive the economy and create jobs. If it were possible to project the future with the central tendency of the monetary policy scenario and monetary policy tools do exist to reverse this adversity, why the tools have not worked before and even prevented the financial crisis? If there is such thing as “monetary policy science”, why it has such poor record and current inability to reverse production and employment adversity? There is no excuse of arguing that additional fiscal measures are needed because they were deployed simultaneously with similar ineffectiveness. Jon Hilsenrath, writing on “New view into Fed’s response to crisis,” on Feb 21, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702303775504579396803024281322?mod=WSJ_hp_LEFTWhatsNewsCollection), analyzes 1865 pages of transcripts of eight formal and six emergency policy meetings at the Fed in 2008 (http://www.federalreserve.gov/monetarypolicy/fomchistorical2008.htm). If there were an infallible science of central banking, models and forecasts would provide accurate information to policymakers on the future course of the economy in advance. Such forewarning is essential to central bank science because of the long lag between the actual impulse of monetary policy and the actual full effects on income and prices many months and even years ahead (Romer and Romer 2004, Friedman 1961, 1953, Culbertson 1960, 1961, Batini and Nelson 2002). Jon Hilsenrath, writing on “New view into Fed’s response to crisis,” on Feb 21, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702303775504579396803024281322?mod=WSJ_hp_LEFTWhatsNewsCollection), analyzed 1865 pages of transcripts of eight formal and six emergency policy meetings at the Fed in 2008 (http://www.federalreserve.gov/monetarypolicy/fomchistorical2008.htm). Jon Hilsenrath demonstrates that Fed policymakers frequently did not understand the current state of the US economy in 2008 and much less the direction of income and prices. The conclusion of Friedman (1953) that monetary impulses increase financial and economic instability because of lags in anticipating needs of policy, taking policy decisions and effects of decisions. This a fortiori true when untested unconventional monetary policy in gargantuan doses shocks the economy and financial markets.
Table I-2, US, Annual CPI Inflation ∆% 1914-2019
Year | Annual ∆% |
1914 | 1.0 |
1915 | 1.0 |
1916 | 7.9 |
1917 | 17.4 |
1918 | 18.0 |
1919 | 14.6 |
1920 | 15.6 |
1921 | -10.5 |
1922 | -6.1 |
1923 | 1.8 |
1924 | 0.0 |
1925 | 2.3 |
1926 | 1.1 |
1927 | -1.7 |
1928 | -1.7 |
1929 | 0.0 |
1930 | -2.3 |
1931 | -9.0 |
1932 | -9.9 |
1933 | -5.1 |
1934 | 3.1 |
1935 | 2.2 |
1936 | 1.5 |
1937 | 3.6 |
1938 | -2.1 |
1939 | -1.4 |
1940 | 0.7 |
1941 | 5.0 |
1942 | 10.9 |
1943 | 6.1 |
1944 | 1.7 |
1945 | 2.3 |
1946 | 8.3 |
1947 | 14.4 |
1948 | 8.1 |
1949 | -1.2 |
1950 | 1.3 |
1951 | 7.9 |
1952 | 1.9 |
1953 | 0.8 |
1954 | 0.7 |
1955 | -0.4 |
1956 | 1.5 |
1957 | 3.3 |
1958 | 2.8 |
1959 | 0.7 |
1960 | 1.7 |
1961 | 1.0 |
1962 | 1.0 |
1963 | 1.3 |
1964 | 1.3 |
1965 | 1.6 |
1966 | 2.9 |
1967 | 3.1 |
1968 | 4.2 |
1969 | 5.5 |
1970 | 5.7 |
1971 | 4.4 |
1972 | 3.2 |
1973 | 6.2 |
1974 | 11.0 |
1975 | 9.1 |
1976 | 5.8 |
1977 | 6.5 |
1978 | 7.6 |
1979 | 11.3 |
1980 | 13.5 |
1981 | 10.3 |
1982 | 6.2 |
1983 | 3.2 |
1984 | 4.3 |
1985 | 3.6 |
1986 | 1.9 |
1987 | 3.6 |
1988 | 4.1 |
1989 | 4.8 |
1990 | 5.4 |
1991 | 4.2 |
1992 | 3.0 |
1993 | 3.0 |
1994 | 2.6 |
1995 | 2.8 |
1996 | 3.0 |
1997 | 2.3 |
1998 | 1.6 |
1999 | 2.2 |
2000 | 3.4 |
2001 | 2.8 |
2002 | 1.6 |
2003 | 2.3 |
2004 | 2.7 |
2005 | 3.4 |
2006 | 3.2 |
2007 | 2.8 |
2008 | 3.8 |
2009 | -0.4 |
2010 | 1.6 |
2011 | 3.2 |
2012 | 2.1 |
2013 | 1.5 |
2014 | 1.6 |
2015 | 0.1 |
2016 | 1.3 |
2017 | 2.1 |
2018 | 2.4 |
2019 | 1.8 |
Source: US Bureau of Labor Statistics https://www.bls.gov/cpi/data.htm
Friedman (1969) finds that the optimal rule for the quantity of money is deflation at a rate that results in a zero nominal interest rate (see Ireland 2003 and Cole and Kocherlakota 1998). Atkeson and Kehoe (2004) argue that central bankers are not inclined to implement policies that could result in deflation because of the interpretation of the Great Depression as closely related to deflation. They use panel data on inflation and growth of real output for 17 countries over more than 100 years. The time-series data for each individual country are broken into five-year events with deflation measured as average negative inflation and depression as average negative growth rate of real output. Atkeson and Kehoe (2004) find that the Great Depression from 1929 to 1934 is the only case of association between deflation and depression without any evidence whatsoever of such relation in any other period. Their conclusion is (Atkeson and Kehoe 2004, 99): “Our finding thus suggests that policymakers’ fear of anticipated policy-induced deflation that would result from following, say, the Friedman rule is greatly overblown.” Their conclusion on the experience of Japan is (Atkeson and Kehoe 2004, 99):
“Since 1960, Japan’s average growth rates have basically fallen monotonically, and since 1970, its average inflation rates have too. Attributing this 40-year slowdown to monetary forces is a stretch. More reasonable, we think, is that much of the slowdown is the natural pattern for a country that was far behind the world leaders and had begun to catch up.”
In the sample of Atkeson and Kehoe (2004), there are only eight five-year periods besides the Great Depression with both inflation and depression. Deflation and depression is shown in 65 cases with 21 of depression without deflation. There is no depression in 65 of 73 five-year periods and there is no deflation in 29 episodes of depression. There is a remarkable result of no depression in 90 percent of deflation episodes. Excluding the Great Depression, there is virtually no relation of deflation and depression. Atkeson and Kehoe (2004, 102) find that the average growth rate of Japan of 1.41 percent in the 1990s is “dismal” when compared with 3.20 percent in the United States but is not “dismal” when compared with 1.61 percent for Italy and 1.84 percent for France, which are also catch-up countries in modern economic growth (see Atkeson and Kehoe 1998). The conclusion of Atkeson and Kehoe (2004), without use of controls, is that there is no association of deflation and depression in their dataset.
Benhabib and Spiegel (2009) use a dataset similar to that of Atkeson and Kehoe (2004) but allowing for nonlinearity and inflation volatility. They conclude that in cases of low and negative inflation an increase of average inflation of 1 percent is associated with an increase of 0.31 percent of average annual growth. The analysis of Benhabib and Spiegel (2009) leads to the significantly different conclusion that inflation and economic performance are strongly associated for low and negative inflation. There is no claim of causality by Atkeson and Kehoe (2004) and Benhabib and Spiegel (2009).
Delfim Netto (1959) partly reprinted in Pelaez (1973) conducted two classical nonparametric tests (Mann 1945, Wallis and Moore 1941; see Kendall and Stuart 1968) with coffee-price data in the period of free markets from 1857 to 1906 with the following conclusions (Pelaez, 1976a, 280):
“First, the null hypothesis of no trend was accepted with high confidence; secondly, the null hypothesis of no oscillation was rejected also with high confidence. Consequently, in the nineteenth century international prices of coffee fluctuated but without long-run trend. This statistical fact refutes the extreme argument of structural weakness of the coffee trade.”
In his classic work on the theory of international trade, Jacob Viner (1937, 563) analyzed the “index of total gains from trade,” or “amount of gain per unit of trade,” denoted as T:
T= (∆Pe/∆Pi)∆Q
Where ∆Pe is the change in export prices, ∆Pi is the change in import prices and ∆Q is the change in export volume. Dorrance (1948, 52) restates “Viner’s index of total gain from trade” as:
“What should be done is to calculate an index of the value (quantity multiplied by price) of exports and the price of imports for any country whose foreign accounts are to be analysed. Then the export value index should be divided by the import price index. The result would be an index which would reflect, for the country concerned, changes in the volume of imports obtainable from its export income (i.e. changes in its "real" export income, measured in import terms). The present writer would suggest that this index be referred to as the ‘income terms of trade’ index to differentiate it from the other indexes at present used by economists.”
What really matters for an export activity especially during modernization is the purchasing value of goods that it exports in terms of prices of imports. For a primary producing country, the purchasing power of exports in acquiring new technology from the country providing imports is the critical measurement. The barter terms of trade of Brazil improved from 1857 to 1906 because international coffee prices oscillated without trend (Delfim Netto 1959) while import prices from the United Kingdom declined at the rate of 0.5 percent per year (Imlah 1958). The accurate measurement of the opportunity afforded by the coffee exporting economy was incomparably greater when considering the purchasing power in British prices of the value of coffee exports, or Dorrance’s (1948) income terms of trade.
The conventional theory that the terms of trade of Brazil deteriorated over the long term is without reality (Pelaez 1976a, 280-281):
“Moreover, physical exports of coffee by Brazil increased at the high average rate of 3.5 per cent per year. Brazil's exchange receipts from coffee-exporting in sterling increased at the average rate of 3.5 per cent per year and receipts in domestic currency at 4.5 per cent per year. Great Britain supplied nearly all the imports of the coffee economy. In the period of the free coffee market, British export prices declined at the rate of 0.5 per cent per year. Thus, the income terms of trade of the coffee economy improved at the relatively satisfactory average rate of 4.0 per cent per year. This is only a lower bound of the rate of improvement of the terms of trade. While the quality of coffee remained relatively constant, the quality of manufactured products improved significantly during the fifty-year period considered. The trade data and the non-parametric tests refute conclusively the long-run hypothesis. The valid historical fact is that the tropical export economy of Brazil experienced an opportunity of absorbing rapidly increasing quantities of manufactures from the "workshop" countries. Therefore, the coffee trade constituted a golden opportunity for modernization in nineteenth-century Brazil.”
Imlah (1958) provides decline of British export prices at 0.5 percent in the nineteenth century and there were no lost decades, depressions or unconventional monetary policies in the highly dynamic economy of England that drove the world’s growth impulse. Inflation in the United Kingdom between 1857 and 1906 is measured by the composite price index of O’Donoghue and Goulding (2004) at minus 7.0 percent or average rate of decline of 0.2 percent per year.
Simon Kuznets (1971) analyzes modern economic growth in his Lecture in Memory of Alfred Nobel:
“The major breakthroughs in the advance of human knowledge, those that constituted dominant sources of sustained growth over long periods and spread to a substantial part of the world, may be termed epochal innovations. And the changing course of economic history can perhaps be subdivided into economic epochs, each identified by the epochal innovation with the distinctive characteristics of growth that it generated. Without considering the feasibility of identifying and dating such economic epochs, we may proceed on the working assumption that modern economic growth represents such a distinct epoch - growth dating back to the late eighteenth century and limited (except in significant partial effects) to economically developed countries. These countries, so classified because they have managed to take adequate advantage of the potential of modern technology, include most of Europe, the overseas offshoots of Western Europe, and Japan—barely one quarter of world population.”
Cameron (1961) analyzes the mechanism by which the Industrial Revolution in Great Britain spread throughout Europe and Cameron (1967) analyzes the financing by banks of the Industrial Revolution in Great Britain. O’Donoghue and Goulding (2004) provide consumer price inflation in England since 1750 and MacFarlane and Mortimer-Lee (1994) analyze inflation in England over 300 years. Lucas (2004) estimates world population and production since the year 1000 with sustained growth of per capita incomes beginning to accelerate for the first time in English-speaking countries and in particular in the Industrial Revolution in Great Britain. The conventional theory is unequal distribution of the gains from trade and technical progress between the industrialized countries and developing economies (Singer 1950, 478):
“Dismissing, then, changes in productivity as a governing factor in changing terms of trade, the following explanation presents itself: the fruits of technical progress may be distributed either to producers (in the form of rising incomes) or to consumers (in the form of lower prices). In the case of manufactured commodities produced in more developed countries, the former method, i.e., distribution to producers through higher incomes, was much more important relatively to the second method, while the second method prevailed more in the case of food and raw material production in the underdeveloped countries. Generalizing, we may say -that technical progress in manufacturing industries showed in a rise in incomes while technical progress in the production of food and raw materials in underdeveloped countries showed in a fall in prices”
Temin (1997, 79) uses a Ricardian trade model to discriminate between two views on the Industrial Revolution with an older view arguing broad-based increases in productivity and a new view concentration of productivity gains in cotton manufactures and iron:
“Productivity advances in British manufacturing should have lowered their prices relative to imports. They did. Albert Imlah [1958] correctly recognized this ‘severe deterioration’ in the net barter terms of trade as a signal of British success, not distress. It is no surprise that the price of cotton manufactures fell rapidly in response to productivity growth. But even the price of woolen manufactures, which were declining as a share of British exports, fell almost as rapidly as the price of exports as a whole. It follows, therefore, that the traditional ‘old-hat’ view of the Industrial Revolution is more accurate than the new, restricted image. Other British manufactures were not inefficient and stagnant, or at least, they were not all so backward. The spirit that motivated cotton manufactures extended also to activities as varied as hardware and haberdashery, arms, and apparel.”
Phyllis Deane (1968, 96) estimates growth of United Kingdom gross national product (GNP) at around 2 percent per year for several decades in the nineteenth century. The facts that the terms of trade of Great Britain deteriorated during the period of epochal innovation and high rates of economic growth while the income terms of trade of the coffee economy of nineteenth-century Brazil improved at the average yearly rate of 4.0 percent from 1857 to 1906 disprove the hypothesis of weakness of trade as an explanation of relatively lower income and wealth. As Temin (1997) concludes, Britain did pass on lower prices and higher quality the benefits of technical innovation. Explanation of late modernization must focus on laborious historical research on institutions and economic regimes together with economic theory, data gathering and measurement instead of grand generalizations of weakness of trade and alleged neocolonial dependence (Stein and Stein 1970, 134-5):
“Great Britain, technologically and industrially advanced, became as important to the Latin American economy as to the cotton-exporting southern United States. [After Independence in the nineteenth century] Latin America fell back upon traditional export activities, utilizing the cheapest available factor of production, the land, and the dependent labor force.”
Summerhill (2015) contributes momentous solid facts and analysis with an ideal method combining economic theory, econometrics, international comparisons, data reconstruction and exhaustive archival research. Summerhill (2015) finds that Brazil committed to service of sovereign foreign and internal debt. Contrary to conventional wisdom, Brazil generated primary fiscal surpluses during most of the Empire until 1889 (Summerhill 2015, 37-8, Figure 2.1). Econometric tests by Summerhill (2015, 19-44) show that Brazil’s sovereign debt was sustainable. Sovereign credibility in the North-Weingast (1989) sense spread to financial development that provided the capital for modernization in England and parts of Europe (see Cameron 1961, 1967). Summerhill (2015, 3, 194-6, Figure 7.1) finds that “Brazil’s annual cost of capital in London fell from a peak of 13.9 percent in 1829 to only 5.12 percent in 1889. Average rates on secured loans in the private sector in Rio, however, remained well above 12 percent through 1850.” Financial development would have financed diversification of economic activities, increasing productivity and wages and ensuring economic growth. Brazil restricted creation of limited liability enterprises (Summerhill 2015, 151-82) that prevented raising capital with issue of stocks and corporate bonds. Cameron (1961) analyzed how the industrial revolution in England spread to France and then to the rest of Europe. The Société Générale de Crédit Mobilier of Émile and Isaac Péreire provided the “mobilization of credit” for the new economic activities (Cameron 1961). Summerhill (2015, 151-9) provides facts and analysis demonstrating that regulation prevented the creation of a similar vehicle for financing modernization by Irineu Evangelista de Souza, the legendary Visconde de Mauá. Regulation also prevented the use of negotiable bearing notes of the Caisse Générale of Jacques Lafitte (Cameron 1961, 118-9). The government also restricted establishment and independent operation of banks (Summerhill 2015, 183-214). Summerhill (2015, 198-9) measures concentration in banking that provided economic rents or a social loss. The facts and analysis of Summerhill (2015) provide convincing evidence in support of the economic theory of regulation, which postulates that regulated entities capture the process of regulation to promote their self-interest. There appears to be a case that excessively centralized government can result in regulation favoring private instead of public interests with adverse effects on economic activity. The contribution of Summerhill (2015) explains why Brazil did not benefit from trade as an engine of growth—as did regions of recent settlement in the vision of nineteenth-century trade and development of Ragnar Nurkse (1959)—partly because of restrictions on financing and incorporation. Professor Rondo E. Cameron, in his memorable A Concise Economic History of the World (Cameron 1989, 307-8), finds that “from a broad spectrum of possible forms of interaction between the financial sector and other sectors of the economy that requires its services, one can isolate three type-cases: (1) that in which the financial sector plays a positive, growth-inducing role; (2) that in which the financial sector is essentially neutral or merely permissive; and (3) that in which inadequate finance restricts or hinders industrial and commercial development.” Summerhill (2015) proves exhaustively that Brazil failed to modernize earlier because of the restrictions of an inadequate institutional financial arrangement plagued by regulatory capture for self-interest.
The experience of the United Kingdom with deflation and economic growth is relevant and rich. Table IE-1 uses yearly percentage changes of the composite index of prices of the United Kingdom of O’Donoghue and Goulding (2004). There are 73 declines of inflation in the 145 years from 1751 to 1896. Prices declined in 50.3 percent of 145 years. Some price declines were quite sharp and many occurred over several years. Table IE-1 also provides yearly percentage changes of the UK composite price index of O’Donoghue and Goulding (2004) from 1929 to 1934. Deflation was much sharper in continuous years in earlier periods than during the Great Depression. The United Kingdom could not have led the world in modern economic growth if there were meaningful causality from deflation to depression.
Table IE-1, United Kingdom, Negative Percentage Changes of Composite Price Index, 1751-1896, 1929-1934, Yearly ∆%
Year | ∆% | Year | ∆% | Year | ∆% | Year | ∆% |
1751 | -2.7 | 1797 | -10.0 | 1834 | -7.8 | 1877 | -0.7 |
1753 | -2.7 | 1798 | -2.2 | 1841 | -2.3 | 1878 | -2.2 |
1755 | -6.0 | 1802 | -23.0 | 1842 | -7.6 | 1879 | -4.4 |
1758 | -0.3 | 1803 | -5.9 | 1843 | -11.3 | 1881 | -1.1 |
1759 | -7.9 | 1806 | -4.4 | 1844 | -0.1 | 1883 | -0.5 |
1760 | -4.5 | 1807 | -1.9 | 1848 | -12.1 | 1884 | -2.7 |
1761 | -4.5 | 1811 | -2.9 | 1849 | -6.3 | 1885 | -3.0 |
1768 | -1.1 | 1814 | -12.7 | 1850 | -6.4 | 1886 | -1.6 |
1769 | -8.2 | 1815 | -10.7 | 1851 | -3.0 | 1887 | -0.5 |
1770 | -0.4 | 1816 | -8.4 | 1857 | -5.6 | 1893 | -0.7 |
1773 | -0.3 | 1819 | -2.5 | 1858 | -8.4 | 1894 | -2.0 |
1775 | -5.6 | 1820 | -9.3 | 1859 | -1.8 | 1895 | -1.0 |
1776 | -2.2 | 1821 | -12.0 | 1862 | -2.6 | 1896 | -0.3 |
1777 | -0.4 | 1822 | -13.5 | 1863 | -3.6 | 1929 | -0.9 |
1779 | -8.5 | 1826 | -5.5 | 1864 | -0.9 | 1930 | -2.8 |
1780 | -3.4 | 1827 | -6.5 | 1868 | -1.7 | 1931 | -4.3 |
1785 | -4.0 | 1828 | -2.9 | 1869 | -5.0 | 1932 | -2.6 |
1787 | -0.6 | 1830 | -6.1 | 1874 | -3.3 | 1933 | -2.1 |
1789 | -1.3 | 1832 | -7.4 | 1875 | -1.9 | 1934 | 0.0 |
1791 | -0.1 | 1833 | -6.1 | 1876 | -0.3 |
Source:
O’Donoghue, Jim and Louise Goulding, 2004. Consumer Price Inflation since 1750. UK Office for National Statistics Economic Trends 604, Mar 2004, 38-46.
There is current interest in past theories of “secular stagnation.” Alvin H. Hansen (1939, 4, 7; see Hansen 1938, 1941; for an early critique see Simons 1942) argues:
“Not until the problem of full employment of our productive resources from the long-run, secular standpoint was upon us, were we compelled to give serious consideration to those factors and forces in our economy which tend to make business recoveries weak and anaemic (sic) and which tend to prolong and deepen the course of depressions. This is the essence of secular stagnation-sick recoveries which die in their infancy and depressions which feed on themselves and leave a hard and seemingly immovable core of unemployment. Now the rate of population growth must necessarily play an important role in determining the character of the output; in other words, the composition of the flow of final goods. Thus a rapidly growing population will demand a much larger per capita volume of new residential building construction than will a stationary population. A stationary population with its larger proportion of old people may perhaps demand more personal services; and the composition of consumer demand will have an important influence on the quantity of capital required. The demand for housing calls for large capital outlays, while the demand for personal services can be met without making large investment expenditures. It is therefore not unlikely that a shift from a rapidly growing population to a stationary or declining one may so alter the composition of the final flow of consumption goods that the ratio of capital to output as a whole will tend to decline.”
In the analysis of Hansen (1939, 3) of secular stagnation, economic progress consists of growth of real income per person driven by growth of productivity. The “constituent elements” of economic progress are “(a) inventions, (b) the discovery and development of new territory and new resources, and (c) the growth of population” (Hansen 1939, 3). Secular stagnation originates in decline of population growth and discouragement of inventions. According to Hansen (1939, 2), US population grew by 16 million in the 1920s but grew by one half or about 8 million in the 1930s with forecasts at the time of Hansen’s writing in 1938 of growth of around 5.3 million in the 1940s. Hansen (1939, 2) characterized demography in the US as “a drastic decline in the rate of population growth. Hansen’s plea was to adapt economic policy to stagnation of population in ensuring full employment. In the analysis of Hansen (1939, 8), population caused half of the growth of US GDP per year. Growth of output per person in the US and Europe was caused by “changes in techniques and to the exploitation of new natural resources.” In this analysis, population caused 60 percent of the growth of capital formation in the US. Declining population growth would reduce growth of capital formation. Residential construction provided an important share of growth of capital formation. Hansen (1939, 12) argues that market power of imperfect competition discourages innovation with prolonged use of obsolete capital equipment. Trade unions would oppose labor-savings innovations. The combination of stagnating and aging population with reduced innovation caused secular stagnation. Hansen (1939, 12) concludes that there is role for public investments to compensate for lack of dynamism of private investment but with tough tax/debt issues.
Table SE1 provides contributions to growth of GDP in the 1930s. These data were not available until much more recently. Residential investment (RSI) contributed 1.03 percentage points to growth of GDP of 8.0 percent in 1939, which is a high percentage of the contribution of gross private domestic investment of 2.39 percentage points. Residential investment contributed 0.42 percentage points to GDP growth of 8.8 percent in 1940 with gross private domestic investment contributing 3.99 percentage points.
Table SE1, US, Contributions to Growth of GDP
GDP ∆% | PCE PP | GDI PP | NRI PP | RSI PP | Net Trade PP | GOVT | |
1930 | -8.5 | -3.96 | -5.18 | -1.84 | -1.50 | -0.31 | 0.94 |
1931 | -6.4 | -2.37 | -4.28 | -3.32 | -0.40 | -0.22 | 0.48 |
1932 | -12.9 | -7.00 | -5.28 | -2.78 | -1.02 | -0.20 | -0.42 |
1933 | -1.3 | -1.79 | 1.16 | -0.44 | -0.24 | -0.11 | -0.52 |
1934 | 10.8 | 5.71 | 2.83 | 1.31 | 0.38 | 0.33 | 1.91 |
1935 | 8.9 | 4.69 | 4.54 | 1.41 | 0.56 | -0.83 | 0.50 |
1936 | 12.9 | 7.68 | 2.58 | 2.10 | 0.47 | 0.24 | 2.44 |
1937 | 5.1 | 2.72 | 2.57 | 1.42 | 0.17 | 0.45 | -0.64 |
1938 | -3.3 | -1.15 | -4.13 | -2.13 | 0.01 | 0.88 | 1.09 |
1939 | 8.0 | 4.11 | 2.39 | 0.71 | 1.03 | 0.07 | 1.41 |
1940 | 8.8 | 3.72 | 3.99 | 1.60 | 0.42 | 0.52 | 0.57 |
GDP ∆%: Annual Growth of GDP; PCE PP: Percentage Points Contributed by Personal Consumption Expenditures (PCE); GDI PP: Percentage Points Contributed by Gross Private Domestic Investment (GDI); NRI PP: Percentage Points Contributed by Nonresidential Investment (NRI); RSI: Percentage Points Contributed by Residential Investment; Net Trade PP: Percentage Points Contributed by Net Exports less Imports of Goods and Services; GOVT PP: Percentage Points Contributed by Government Consumption and Gross Investment
Source: Bureau of Economic Analysis
http://www.bea.gov/iTable/index_nipa.cfm
Table ES2 provides percentage shares of GDP in 1929, 1939, 1940, 2006 and 2015. The share of residential investment was 3.9 percent in 1929, 3.4 percent in 1939 and 6.0 percent in 2006 at the peak of the real estate boom. The share of residential investment in GDP has not been very high historically.
Table ES2, Percentage Shares in GDP
1929 | 1939 | 1940 | 2006 | 2015 | |
GDP | 100.00 | 100.00 | 100.00 | 100.00 | 100.00 |
PCE | 74.0 | 71.9 | 69.2 | 67.1 | 68.4 |
GDI | 16.4 | 10.9 | 14.2 | 19.3 | 16.8 |
NRI | 11.1 | 7.3 | 8.3 | 12.8 | 12.8 |
RSI | 3.9 | 3.4 | 3.5 | 6.0 | 3.4 |
Net Trade | 0.4 | 0.9 | 1.4 | -5.6 | -3.0 |
GOVT | 9.2 | 16.3 | 15.2 | 19.1 | 17.8 |
PCE: Personal Consumption Expenditures; GDI: Gross Domestic Investment; NRI: Nonresidential Investment; RSI: Residential Investment; Net Trade: Net Exports less Imports of Goods and Services; GOVT: Government Consumption and Gross Investment
Source: Bureau of Economic Analysis
PCE: Personal Consumption Expenditures; GDI: Gross Private Domestic Investment; NRI: Nonresidential Investment; RSI: Residential Investment; Net Trade: Net Exports less Imports of Goods and Services; GOVT: Government Consumption and Gross Investment
Source: Bureau of Economic Analysis
http://www.bea.gov/iTable/index_nipa.cfm
An interpretation of the New Deal is that fiscal stimulus must be massive in recovering growth and employment and that it should not be withdrawn prematurely to avoid a sharp second contraction as it occurred in 1937 (Christina Romer 2009). Proposals for another higher dose of stimulus explain the current weakness by insufficient fiscal expansion and warn that failure to spend more can cause another contraction as in 1937. According to a different interpretation, private hours worked declined by 25 percent by 1939 compared with the level in 1929, suggesting that the economy fell to a lower path of expansion than in 1929 (works by Harold Cole and Lee Ohanian (1999) (cited in Pelaez and Pelaez, Regulation of Banks and Finance, 215-7). Major real variables of output and employment were below trend by 1939: -26.8 percent for GNP, -25.4 percent for consumption, -51 percent for investment and -25.6 percent for hours worked. Surprisingly, total factor productivity increased by 3.1 percent and real wages by 21.8 percent (Cole and Ohanian 1999). The policies of the Roosevelt administration encouraged increasing unionization to maintain high wages with lower hours worked and high prices by lax enforcement of antitrust law to encourage cartels or collusive agreements among producers. The encouragement by the government of labor bargaining by unions and higher prices by collusion depressed output and employment throughout the 1930s until Roosevelt abandoned the policies during World War II after which the economy recovered full employment (Cole and Ohanian 1999). The fortunate ones who worked during the New Deal received higher real wages at the expense of many who never worked again. In a way, the administration behaved like the father of the unionized workers and the uncle of the collusive rich, neglecting the majority in the middle. Inflation-adjusted GDP increased by 10.8 percent in 1934, 8.9 percent in 1935, 12.9 percent in 1936 but only 5.1 percent in 1937, contracting by -3.3 percent in 1938 (US Bureau of Economic Analysis cited in Pelaez and Pelaez, Financial Regulation after the Global Recession, 151, Globalization and the State, Vol. II, 206). The competing explanation is that the economy did not decline from 1937 to 1938 because of lower government spending in 1937 but rather because of the expansion of unions promoted by the New Deal and increases in tax rates (Thomas Cooley and Lee Ohanian 2010). Government spending adjusted for inflation fell only 0.7 percent in 1936 and 1937 and could not explain the decline of GDP by 3.4 percent in 1938. In 1936, the administration imposed a tax on retained profits not distributed to shareholders according to a sliding scale of 7 percent for retaining 1 percent of total net income up to 27 percent for retaining 70 percent of total net income, increasing costs of investment that were mostly financed in that period with retained earnings (Cooley and Ohanian 2010). The tax rate on dividends jumped from 10.1 percent in 1929 to 15.9 percent in 1932 and doubled by 1936. A recent study finds that “tax rates on dividends rose dramatically during the 1930s and imply significant declines in investment and equity values and nontrivial declines in GDP and hours of work” (Ellen McGrattan 2010), explaining a significant part of the decline of 26 percent in business fixed investment in 1937-1938. The National Labor Relations Act of 1935 caused an increase in union membership from 12 percent in 1934 to 25 percent in 1938. The alternative lesson from the 1930s is that capital income taxes and higher unionization caused increases in business costs that perpetuated job losses of the recession with current risks of repeating the 1930s (Cooley and Ohanian 1999).
In the analysis of Hansen (1939, 3) of secular stagnation, economic progress consists of growth of real income per person driven by growth of productivity. The “constituent elements” of economic progress are “(a) inventions, (b) the discovery and development of new territory and new resources, and (c) the growth of population” (Hansen 1939, 3). Secular stagnation originates in decline of population growth and discouragement of inventions. According to Hansen (1939, 2), US population grew by 16 million in the 1920s but grew by one half or about 8 million in the 1930s with forecasts at the time of Hansen’s writing in 1938 of growth of around 5.3 million in the 1940s. Hansen (1939, 2) characterized demography in the US as “a drastic decline in the rate of population growth. Hansen’s plea was to adapt economic policy to stagnation of population in ensuring full employment. In the analysis of Hansen (1939, 8), population caused half of the growth of US GDP per year. Growth of output per person in the US and Europe was caused by “changes in techniques and to the exploitation of new natural resources.” In this analysis, population caused 60 percent of the growth of capital formation in the US. Declining population growth would reduce growth of capital formation. Residential construction provided an important share of growth of capital formation. Hansen (1939, 12) argues that market power of imperfect competition discourages innovation with prolonged use of obsolete capital equipment. Trade unions would oppose labor-savings innovations. The combination of stagnating and aging population with reduced innovation caused secular stagnation. Hansen (1939, 12) concludes that there is role for public investments to compensate for lack of dynamism of private investment but with tough tax/debt issues.
The current application of Hansen’s (1938, 1939, 1941) proposition argues that secular stagnation occurs because full employment equilibrium can be attained only with negative real interest rates between minus 2 and minus 3 percent. Professor Lawrence H. Summers (2013Nov8) finds that “a set of older ideas that went under the phrase secular stagnation are not profoundly important in understanding Japan’s experience in the 1990s and may not be without relevance to America’s experience today” (emphasis added). Summers (2013Nov8) argues there could be an explanation in “that the short-term real interest rate that was consistent with full employment had fallen to -2% or -3% sometime in the middle of the last decade. Then, even with artificial stimulus to demand coming from all this financial imprudence, you wouldn’t see any excess demand. And even with a relative resumption of normal credit conditions, you’d have a lot of difficulty getting back to full employment.” The US economy could be in a situation where negative real rates of interest with fed funds rates close to zero as determined by the Federal Open Market Committee (FOMC) do not move the economy to full employment or full utilization of productive resources. Summers (2013Oct8) finds need of new thinking on “how we manage an economy in which the zero nominal interest rates is a chronic and systemic inhibitor of economy activity holding our economies back to their potential.”
Former US Treasury Secretary Robert Rubin (2014Jan8) finds three major risks in prolonged unconventional monetary policy of zero interest rates and quantitative easing: (1) incentive of delaying action by political leaders; (2) “financial moral hazard” in inducing excessive exposures pursuing higher yields of risker credit classes; and (3) major risks in exiting unconventional policy. Rubin (2014Jan8) proposes reduction of deficits by structural reforms that could promote recovery by improving confidence of business attained with sound fiscal discipline.
Professor John B. Taylor (2014Jan01, 2014Jan3) provides clear thought on the lack of relevance of Hansen’s contention of secular stagnation to current economic conditions. The application of secular stagnation argues that the economy of the US has attained full-employment equilibrium since around 2000 only with negative real rates of interest of minus 2 to minus 3 percent. At low levels of inflation, the so-called full-employment equilibrium of negative interest rates of minus 2 to minus 3 percent cannot be attained and the economy stagnates. Taylor (2014Jan01) analyzes multiple contradictions with current reality in this application of the theory of secular stagnation:
- Secular stagnation would predict idle capacity, in particular in residential investment when fed fund rates were fixed at 1 percent from Jun 2003 to Jun 2004. Taylor (2014Jan01) finds unemployment at 4.4 percent with house prices jumping 7 percent from 2002 to 2003 and 14 percent from 2004 to 2005 before dropping from 2006 to 2007. GDP prices doubled from 1.7 percent to 3.4 percent when interest rates were low from 2003 to 2005.
- Taylor (2014Jan01, 2014Jan3) finds another contradiction in the application of secular stagnation based on low interest rates because of savings glut and lack of investment opportunities. Taylor (2009) shows that there was no savings glut. The savings rate of the US in the past decade is significantly lower than in the 1980s.
- Taylor (2014Jan01, 2014Jan3) finds another contradiction in the low ratio of investment to GDP currently and reduced investment and hiring by US business firms.
- Taylor (2014Jan01, 2014Jan3) argues that the financial crisis and global recession were caused by weak implementation of existing regulation and departure from rules-based policies.
- Taylor (2014Jan01, 2014Jan3) argues that the recovery from the global recession was constrained by a change in the regime of regulation and fiscal/monetary policies.
In revealing research, Edward P. Lazear and James R. Spletzer (2012JHJul22) use the wealth of data in the valuable database and resources of the Bureau of Labor Statistics (https://www.bls.gov/data/) in providing clear thought on the nature of the current labor market of the United States. The critical issue of analysis and policy currently is whether unemployment is structural or cyclical. Structural unemployment could occur because of (1) industrial and demographic shifts and (2) mismatches of skills and job vacancies in industries and locations. Consider the aggregate unemployment rate, Y, expressed in terms of share si of a demographic group in an industry i and unemployment rate yi of that demographic group (Lazear and Spletzer 2012JHJul22, 5-6):
Y = ∑isiyi (1)
This equation can be decomposed for analysis as (Lazear and Spletzer 2012JHJul22, 6):
∆Y = ∑i∆siy*i + ∑i∆yis*i (2)
The first term in (2) captures changes in the demographic and industrial composition of the economy ∆si multiplied by the average rate of unemployment y*i , or structural factors. The second term in (2) captures changes in the unemployment rate specific to a group, or ∆yi, multiplied by the average share of the group s*i, or cyclical factors. There are also mismatches in skills and locations relative to available job vacancies. A simple observation by Lazear and Spletzer (2012JHJul22) casts intuitive doubt on structural factors: the rate of unemployment jumped from 4.4 percent in the spring of 2007 to 10 percent in October 2009. By nature, structural factors should be permanent or occur over relative long periods. The revealing result of the exhaustive research of Lazear and Spletzer (2012JHJul22) is:
“The analysis in this paper and in others that we review do not provide any compelling evidence that there have been changes in the structure of the labor market that are capable of explaining the pattern of persistently high unemployment rates. The evidence points to primarily cyclic factors.”
Table I-4b and Chart I-12-b provide the US labor force participation rate or percentage of the labor force in population. It is not likely that simple demographic trends caused the sharp decline during the global recession and failure to recover earlier levels. The civilian labor force participation rate dropped from the peak of 66.9 percent in Jul 2006 to 62.6 percent in Dec 2013, 62.5 percent in Dec 2014, 62.4 percent in Dec 2015 and 62.4 in Dec 2016. The civilian labor force participation rate reached 62.4 in Dec 2017, and 63.1 percent in 2019. The civilian labor force participation rate was at 62.9 percent in Nov 2018 and 62.8 percent in Dec 2018. The civilian labor force participation was 63.0 in Dec 2019. The civilian labor force participation rate was 61.7 in Dec 2020. The civilian labor force participation rate was 63.7 percent on an annual basis in 1979 and 63.4 percent in Dec 1980 and Dec 1981, reaching even 62.9 percent in both Apr and May 1979. The civilian labor force participation rate jumped with the recovery to 64.8 percent on an annual basis in 1985 and 65.9 percent in Jul 1985. Structural factors cannot explain these sudden changes vividly shown visually in the final segment of Chart I-12b. Seniors would like delay their retiring especially because of the adversities of financial repression on their savings. Labor force statistics are capturing the disillusion of potential workers with their chances in finding a job in what Lazear and Spletzer (2012JHJul22) characterize as accentuated cyclical factors. The argument that anemic population growth causes “secular stagnation” in the US (Hansen 1938, 1939, 1941) is as misplaced currently as in the late 1930s (for early dissent see Simons 1942). There is currently population growth in the ages of 16 to 24 years but not enough job creation and discouragement of job searches for all ages (https://cmpassocregulationblog.blogspot.com/2020/10/total-nonfarm-hires-jump-from-5864.html and earlier https://cmpassocregulationblog.blogspot.com/2020/09/new-nonfarm-hires-of-6.html). “Secular stagnation” would be a process over many years and not from one year to another. This is merely another case of theory without reality with dubious policy proposals.
Table I-4b, US, Labor Force Participation Rate, Percent of Labor Force in Population, NSA, 1979-2020
Year | Jun | Jul | Aug | Sep | Oct | Dec | Annual |
1979 | 64.5 | 64.9 | 64.5 | 63.8 | 64.0 | 63.8 | 63.7 |
1980 | 64.6 | 65.1 | 64.5 | 63.6 | 63.9 | 63.4 | 63.8 |
1981 | 64.6 | 65.0 | 64.6 | 63.5 | 64.0 | 63.4 | 63.9 |
1982 | 64.8 | 65.3 | 64.9 | 64.0 | 64.1 | 63.8 | 64.0 |
1983 | 65.1 | 65.4 | 65.1 | 64.3 | 64.1 | 63.8 | 64.0 |
1984 | 65.5 | 65.9 | 65.2 | 64.4 | 64.6 | 64.3 | 64.4 |
1985 | 65.5 | 65.9 | 65.4 | 64.9 | 65.1 | 64.6 | 64.8 |
1986 | 66.3 | 66.6 | 66.1 | 65.3 | 65.5 | 65.0 | 65.3 |
1987 | 66.3 | 66.8 | 66.5 | 65.5 | 65.9 | 65.5 | 65.6 |
1988 | 66.7 | 67.1 | 66.8 | 65.9 | 66.1 | 65.9 | 65.9 |
1989 | 67.4 | 67.7 | 67.2 | 66.3 | 66.6 | 66.3 | 66.5 |
1990 | 67.4 | 67.7 | 67.1 | 66.4 | 66.5 | 66.1 | 66.5 |
1991 | 67.2 | 67.3 | 66.6 | 66.1 | 66.1 | 65.8 | 66.2 |
1992 | 67.6 | 67.9 | 67.2 | 66.3 | 66.2 | 66.1 | 66.4 |
1993 | 67.3 | 67.5 | 67.0 | 66.1 | 66.4 | 66.2 | 66.3 |
1994 | 67.2 | 67.5 | 67.2 | 66.5 | 66.8 | 66.5 | 66.6 |
1995 | 67.2 | 67.7 | 67.1 | 66.5 | 66.7 | 66.2 | 66.6 |
1996 | 67.4 | 67.9 | 67.2 | 66.8 | 67.1 | 66.7 | 66.8 |
1997 | 67.8 | 68.1 | 67.6 | 67.0 | 67.1 | 67.0 | 67.1 |
1998 | 67.7 | 67.9 | 67.3 | 67.0 | 67.1 | 67.0 | 67.1 |
1999 | 67.7 | 67.9 | 67.3 | 66.8 | 67.0 | 67.0 | 67.1 |
2000 | 67.7 | 67.6 | 67.2 | 66.7 | 66.9 | 67.0 | 67.1 |
2001 | 67.2 | 67.4 | 66.8 | 66.6 | 66.7 | 66.6 | 66.8 |
2002 | 67.1 | 67.2 | 66.8 | 66.6 | 66.6 | 66.2 | 66.6 |
2003 | 67.0 | 66.8 | 66.3 | 65.9 | 66.1 | 65.8 | 66.2 |
2004 | 66.5 | 66.8 | 66.2 | 65.7 | 66.0 | 65.8 | 66.0 |
2005 | 66.5 | 66.8 | 66.5 | 66.1 | 66.2 | 65.9 | 66.0 |
2006 | 66.7 | 66.9 | 66.5 | 66.1 | 66.4 | 66.3 | 66.2 |
2007 | 66.6 | 66.8 | 66.1 | 66.0 | 66.0 | 65.9 | 66.0 |
2008 | 66.6 | 66.8 | 66.4 | 65.9 | 66.1 | 65.7 | 66.0 |
2009 | 66.2 | 66.2 | 65.6 | 65.0 | 64.9 | 64.4 | 65.4 |
2010 | 65.1 | 65.3 | 65.0 | 64.6 | 64.4 | 64.1 | 64.7 |
2011 | 64.5 | 64.6 | 64.3 | 64.2 | 64.1 | 63.8 | 64.1 |
2012 | 64.3 | 64.3 | 63.7 | 63.6 | 63.8 | 63.4 | 63.7 |
2013 | 64.0 | 64.0 | 63.4 | 63.2 | 62.9 | 62.6 | 63.2 |
2014 | 63.4 | 63.5 | 63.0 | 62.8 | 63.0 | 62.5 | 62.9 |
2015 | 63.1 | 63.2 | 62.7 | 62.3 | 62.5 | 62.4 | 62.7 |
2016 | 63.2 | 63.4 | 62.9 | 62.8 | 62.8 | 62.4 | 62.8 |
2017 | 63.3 | 63.5 | 63.0 | 63.0 | 62.7 | 62.4 | 62.9 |
2018 | 63.4 | 63.5 | 62.7 | 62.7 | 62.9 | 62.8 | 62.9 |
2019 | 63.4 | 63.6 | 63.2 | 63.1 | 63.3 | 63.0 | 63.1 |
2020 | 61.8 | 62.0 | 61.8 | 61.4 | 61.7 |
Source: US Bureau of Labor Statistics
Chart I-12b, US, Labor Force Participation Rate, Percent of Labor Force in Population, NSA, 1979-2020
Source: Bureau of Labor Statistics
The magnitude of the stress in US labor markets is magnified by the increase in the civilian noninstitutional population of the United States from 231.958 million in Jul 2007 to 260.925 million in Oct 2020 or by 28.967 million (https://www.bls.gov/data/). The number with full-time jobs in Oct 2020 is 124.165 million, 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, which is higher by 0.946 million relative to the peak of 123.219 million in Jul 2007. The ratio of full-time jobs of 123.219 million in Jul 2007 to civilian noninstitutional population of 231.958 million was 53.1 percent. If that ratio had remained the same, there would be 138.551 million full-time jobs with population of 260.925 million in Oct 2020 (0.531 x 260.925) or 14.386 million fewer full-time jobs relative to actual 124.165 million. There appear to be around 15 million fewer full-time jobs in the US than before the global recession while population increased around 29 million. Mediocre GDP growth is the main culprit of the fractured US labor market augmented in the global recession, with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event.
There is current interest in past theories of “secular stagnation.” Alvin H. Hansen (1939, 4, 7; see Hansen 1938, 1941; for an early critique see Simons 1942) argues:
“Not until the problem of full employment of our productive resources from the long-run, secular standpoint was upon us, were we compelled to give serious consideration to those factors and forces in our economy which tend to make business recoveries weak and anaemic (sic) and which tend to prolong and deepen the course of depressions. This is the essence of secular stagnation-sick recoveries which die in their infancy and depressions which feed on them-selves and leave a hard and seemingly immovable core of unemployment. Now the rate of population growth must necessarily play an important role in determining the character of the output; in other words, the com-position of the flow of final goods. Thus a rapidly growing population will demand a much larger per capita volume of new residential building construction than will a stationary population. A stationary population with its larger proportion of old people may perhaps demand more personal services; and the composition of consumer demand will have an important influence on the quantity of capital required. The demand for housing calls for large capital outlays, while the demand for personal services can be met without making large investment expenditures. It is therefore not unlikely that a shift from a rapidly growing population to a stationary or declining one may so alter the composition of the final flow of consumption goods that the ratio of capital to output as a whole will tend to decline.”
The argument that anemic population growth causes “secular stagnation” in the US (Hansen 1938, 1939, 1941) is as misplaced currently as in the late 1930s (for early dissent see Simons 1942). This is merely another case of theory without reality with dubious policy proposals.
Inferior performance of the US economy and labor markets, during cyclical slow growth not secular stagnation, is the critical current issue of analysis and policy design.
Chart I-20, US, Full-time Employed, Thousands, NSA, 2001-2020
Sources: US Bureau of Labor Statistics
Chart I-20A provides the noninstitutional civilian population of the United States from 2001 to 2020. There is clear trend of increase of the population while the number of full-time jobs collapsed after 2008 with insufficient recovery as shown in the preceding Chart I-20.
Chart I-20A, US, Noninstitutional Civilian Population, Thousands, 2001-2020
Sources: US Bureau of Labor Statistics
Chart I-20B provides number of full-time jobs in the US from 1968 to 2020. There were multiple recessions followed by expansions without contraction of full-time jobs and without recovery as during the period after 2008. The problem is specific of the current cycle and not secular.
Chart I-20B, US, Full-time Employed, Thousands, NSA, 1968-2020
Sources: US Bureau of Labor Statistics
Chart I-20C provides the noninstitutional civilian population of the United States from 1968 to 2020. Population expanded at a relatively constant rate of increase with the assurance of creation of full-time jobs that has been broken since 2008.
Chart I-20C, US, Noninstitutional Civilian Population, Thousands, 1968-2020
Sources: US Bureau of Labor Statistics
Table EMP provides the comparison between the labor market in the current whole cycle from 2007 to 2019 and the whole cycle from 1979 to 1989. In the entire cycle from 2007 to 2019, the number employed increased 11.491 million, full-time employed increased 9.506 million, part-time for economic reasons increased 0.006 million and population increased 27.308 million. The number employed increased 7.9 percent, full-time employed increased 7.9 percent, part-time for economic reasons increased 0.1 percent and population increased 11.8 percent. There is sharp contrast with the contractions of the 1980s and with most economic history of the United States. In the whole cycle from 1979 to 1989, the number employed increased 18.518 million, full-time employed increased 14.715 million, part-time for economic reasons increased 1.317 million and population increased 21.530 million. In the entire cycle from 1979 to 1989, the number employed increased 18.7 percent, full-time employed increased 17.8 percent, part-time for economic reasons increased 36.8 percent and population increased 13.1 percent. The difference between the 1980s and the current cycle after 2007 is in the high rate of growth after the contraction that maintained trend growth around 3.0 percent for the entire cycle and per capital growth at 2.0 percent. The evident fact is that current weakness in labor markets originates in cyclical slow growth and not in imaginary secular stagnation.
Table EMP, US, Annual Level of Employed, Full-Time Employed, Employed Part-Time for Economic Reasons and Noninstitutional Civilian Population, Millions
Employed | Full-Time Employed | Part Time Economic Reasons | Noninstitutional Civilian Population | |
2000s | ||||
2000 | 136.891 | 113.846 | 3.227 | 212.577 |
2001 | 136.933 | 113.573 | 3.715 | 215.092 |
2002 | 136.485 | 112.700 | 4.213 | 217.570 |
2003 | 137.736 | 113.324 | 4.701 | 221.168 |
2004 | 139.252 | 114.518 | 4.567 | 223.357 |
2005 | 141.730 | 117.016 | 4.350 | 226.082 |
2006 | 144.427 | 119.688 | 4.162 | 228.815 |
2007 | 146.047 | 121.091 | 4.401 | 231.867 |
2008 | 145.362 | 120.030 | 5.875 | 233.788 |
2009 | 139.877 | 112.634 | 8.913 | 235.801 |
2010 | 139.064 | 111.714 | 8.874 | 237.830 |
2011 | 139.869 | 112.556 | 8.560 | 239.618 |
2012 | 142.469 | 114.809 | 8.122 | 243.284 |
2013 | 143.929 | 116.314 | 7.935 | 245.679 |
2014 | 146.305 | 118.718 | 7.213 | 247.947 |
2015 | 148.834 | 121.492 | 6.371 | 250.801 |
2016 | 151.436 | 123.761 | 5.943 | 253.538 |
2017 | 153.337 | 125.967 | 5.250 | 255.079 |
2018 | 155.761 | 128.572 | 4.778 | 257.791 |
2019 | 157.538 | 130.597 | 4.407 | 259.175 |
∆2007-2019 | 11.491 | 9.506 | 0.006 | 27.308 |
∆% 2007-2019 | 7.9 | 7.9 | 0.1 | 11.8 |
1980s | ||||
1979 | 98.824 | 82.654 | 3.577 | 164.863 |
1980 | 99.303 | 82.562 | 4.321 | 167.745 |
1981 | 100.397 | 83.243 | 4.768 | 170.130 |
1982 | 99.526 | 81.421 | 6.170 | 172.271 |
1983 | 100.834 | 82.322 | 6.266 | 174.215 |
1984 | 105.005 | 86.544 | 5.744 | 176.383 |
1985 | 107.150 | 88.534 | 5.590 | 178.206 |
1986 | 109.597 | 90.529 | 5.588 | 180.587 |
1987 | 112.440 | 92.957 | 5.401 | 182.753 |
1988 | 114.968 | 95.214 | 5.206 | 184.613 |
1989 | 117.342 | 97.369 | 4.894 | 186.393 |
∆1979-1989 | 18.518 | 14.715 | 1.317 | 21.530 |
∆% 1979-1989 | 18.7 | 17.8 | 36.8 | 13.1 |
Source: Bureau of Labor Statistics
The total noninstitutional civilian population (ICP) continued to increase during and after the global recession. There is the same disastrous labor market with decline for all in employment (EMP), civilian labor force (CLF), civilian labor force participation rate (CLFP) and employment population ratio (EPOP). There are only increases for unemployment (UNE) and unemployment rate (UNER). The application of the theory of secular stagnation to the US economy and labor markets is void of reality in the form of key facts, which are best explained by accentuated cyclic factors analyzed by Lazear and Spletzer (2012JHJul22).
Table Summary Total, US, Total Noninstitutional Civilian Population, Full-time Employment, Employment, Civilian Labor Force, Civilian Labor Force Participation Rate, Employment Population Ratio, Unemployment, NSA, Millions and Percent
ICP | FTE | EMP | CLF | CLFP | EPOP | UNE | |
2006 | 228.8 | 119.7 | 144.4 | 151.4 | 66.2 | 63.1 | 7.0 |
2009 | 235.8 | 112.6 | 139.9 | 154.1 | 65.4 | 59.3 | 14.3 |
2012 | 243.3 | 114.8 | 142.5 | 155.0 | 63.7 | 58.6 | 12.5 |
2013 | 245.7 | 116.3 | 143.9 | 155.4 | 63.2 | 58.6 | 11.5 |
2014 | 247.9 | 118.7 | 146.3 | 155.9 | 62.9 | 59.0 | 9.6 |
2015 | 250.8 | 121.5 | 148.8 | 157.1 | 62.7 | 59.3 | 8.3 |
2016 | 253.5 | 123.8 | 151.4 | 159.2 | 62.8 | 59.7 | 7.8 |
2017 | 255.1 | 126.0 | 153.3 | 160.3 | 62.9 | 60.1 | 7.0 |
2018 | 257.8 | 128.6 | 155.8 | 162.1 | 62.9 | 60.4 | 6.3 |
2019 | 259.2 | 130.6 | 157.5 | 163.5 | 63.1 | 60.8 | 6.0 |
12/07 | 233.2 | 121.0 | 146.3 | 153.7 | 65.9 | 62.8 | 7.4 |
9/09 | 236.3 | 112.0 | 139.1 | 153.6 | 65.0 | 58.9 | 14.5 |
10/20 | 260.9 | 124.2 | 150.4 | 160.1 | 61.7 | 57.7 | 10.6 |
ICP: Total Noninstitutional Civilian Population; FTE: Full-time Employment Level, EMP: Total Employment Level; CLF: Civilian Labor Force; CLFP: Civilian Labor Force Participation Rate; EPOP: Employment Population Ratio; UNE: Unemployment
Source: Bureau of Labor Statistics
The same situation is present in the labor market for young people in ages 16 to 24 years with data in Table Summary Youth. The youth noninstitutional civilian population (ICP) continued to increase during and after the global recession. There is the same disastrous labor market with decline for young people in employment (EMP), civilian labor force (CLF), civilian labor force participation rate (CLFP) and employment population ratio (EPOP). There are only increases for unemployment of young people (UNE) and youth unemployment rate (UNER). If aging were a factor of secular stagnation, growth of population of young people would attract a premium in remuneration in labor markets. The sad fact is that young people are also facing tough labor markets. The application of the theory of secular stagnation to the US economy and labor markets is void of reality in the form of key facts, which are best explained by accentuated cyclic factors analyzed by Lazear and Spletzer (2012JHJul22).
ICP | EMP | CLF | CLFP | EPOP | UNE | UNER | |
2006 | 36.9 | 20.0 | 22.4 | 60.6 | 54.2 | 2.4 | 10.5 |
2009 | 37.6 | 17.6 | 21.4 | 56.9 | 46.9 | 3.8 | 17.6 |
2012 | 38.8 | 17.8 | 21.3 | 54.9 | 46.0 | 3.5 | 16.2 |
2013 | 38.8 | 18.1 | 21.4 | 55.0 | 46.5 | 3.3 | 15.5 |
2014 | 38.7 | 18.4 | 21.3 | 55.0 | 47.6 | 2.9 | 13.4 |
2015 | 38.6 | 18.8 | 21.2 | 55.0 | 48.6 | 2.5 | 11.6 |
2016 | 38.4 | 19.0 | 21.2 | 55.2 | 49.4 | 2.2 | 10.4 |
2017 | 38.2 | 19.2 | 21.2 | 55.5 | 50.3 | 2.0 | 9.2 |
2018 | 38.0 | 19.2 | 21.0 | 55.2 | 50.5 | 1.8 | 8.6 |
2019 | 37.7 | 19.3 | 21.1 | 55.9 | 51.2 | 1.8 | 8.4 |
12/07 | 37.5 | 19.4 | 21.7 | 57.8 | 51.6 | 2.3 | 10.7 |
9/09 | 37.6 | 17.0 | 20.7 | 55.2 | 45.1 | 3.8 | 18.2 |
10/20 | 37.5 | 18.2 | 20.0 | 54.8 | 48.6 | 2.3 | 11.2 |
ICP: Youth Noninstitutional Civilian Population; EMP: Youth Employment Level; CLF: Youth Civilian Labor Force; CLFP: Youth Civilian Labor Force Participation Rate; EPOP: Youth Employment Population Ratio; UNE: Unemployment; UNER: Youth Unemployment Rate
Source: Bureau of Labor Statistics
The eminent economist and historian Professor Rondo E. Cameron (1989, 3) searches for the answer of “why are some nations rich and others poor?” by analyzing economic history since Paleolithic times. Cameron (1989, 4) argues that:
“Policymakers and their staffs of experts, faced with the responsibility of proposing and implementing policies for development, frequently shrug off the potential contributions of historical analysis to the solution of their problems with the observation that the contemporary situation is unique and therefore history is irrelevant to their concerns. Such an attitude contains a double fallacy. In the first place, those who are ignorant of the past are not qualified to generalize about it. Second, it implicitly denies the uniformity of nature, including human behavior and the behavior of social institutions—an assumption on which all scientific inquiry is founded. Such attitudes reveal how easy it is, without historical perspective, to mistake the symptoms of a problem for its causes.”
Scholars detached from practical issues of economic policy are more likely to discover sound knowledge (Cohen and Nagel 1934). There is troublesome sacrifice of rigorous scientific objectivity in cutting the economic past by a procrustean bed fitting favored current economic policies.
Nicholas Georgescu-Rogen (1960, 1) reprinted in Pelaez (1973) argues that “the agrarian economy has to this day remained a reality without theory.” The economic history of Latin America shares with the relation of deflation and unconventional monetary policy and secular stagnation when the event is cyclical slow growth a more frustrating intellectual misfortune: theory without reality. MacFarlane and Mortimer-Lee (1994, 159) quote in a different context a phrase by Thomas Henry Huxley in the President’s Address to the British Association for the Advancement of Science on Sep 14, 1870 that is appropriate to these issues: “The great tragedy of science—the slaying of a beautiful hypothesis by an ugly fact.” There may be current relevance in another quote from Thomas Henry Huxley: “The deepest sin against the human mind is to believe things without evidence.”
II Rules, Discretionary Authorities and Slow Productivity Growth. The Bureau of Labor Statistics (BLS) of the Department of Labor provides the quarterly report on productivity and costs. The operational definition of productivity used by the BLS is (https://www.bls.gov/news.release/pdf/prod2.pdf 1): “Labor productivity, or output per hour, is calculated by dividing an index of real output by an index of hours worked of all persons, including employees, proprietors, and unpaid family workers.” The BLS has revised the estimates for productivity and unit costs. Table II-1 provides estimates for IIIQ2020 and revision of the estimates for IIQ2020 and IQ2020 together with data for nonfarm business sector productivity and unit labor costs in seasonally adjusted annual equivalent (SAAE) rate and the percentage change from the same quarter a year earlier. Reflecting increase in output at 43.5 percent and increase at 36.8 percent in hours worked, nonfarm business sector labor productivity increased at the SAAE rate of 4.9 percent in IIIQ2020, as shown in column 2 “IIIQ2020 SAEE.” The increase of labor productivity from IIIQ2019 to IIIQ2020 was 4.1 percent, reflecting decrease in output of 3.4 percent and decrease of hours worked of 7.2 percent, as shown in column 3 “IIIQ2020 YOY.” Hours worked decreased from minus 6.1 percent in IQ2020 to minus 42.9 percent in IIQ2020 and increased at 36.8 percent in IIIQ2020 while output growth decreased from minus 6.4 percent in IQ2020 at SAAE to minus 36.8 percent in IIQ2020, increasing at 43.5 percent in IIIQ2020. The BLS defines unit labor costs as (https://www.bls.gov/news.release/pdf/prod2.pdf 1): “BLS calculates unit labor costs as the ratio of hourly compensation to labor productivity. Increases in hourly compensation tend to increase unit labor costs and increases in output per hour tend to reduce them.” Unit labor costs decreased at the SAAE rate of 8.9 percent in IIIQ2020 and increased 2.5 percent in IIIQ2020 relative to III2019. Hourly compensation decreased at the SAAE rate of 4.4 percent in IIIQ2020, which deflating by the estimated inflation increase SAAE rate in IIIQ2020 results in decrease of real hourly compensation at 9.1 percent. Real hourly compensation increased 5.3 percent in IIIQ2020 relative to IIIQ2019.
Table II-1, US, Nonfarm Business Sector Productivity and Costs %
IIIQ2020 SAAE | IIIQ2020 YOY | IIQ2020 SAAE | IIQ2020 YOY | IQ2020 SAAE | IQ2020 YOY | |
Productivity | 4.9 | 4.1 | 10.6 | 2.9 | -0.3 | 0.9 |
Output | 43.5 | -3.4 | -36.8 | -11.1 | -6.4 | 0.1 |
Hours | 36.8 | -7.2 | -42.9 | -13.6 | -6.1 | -0.8 |
Hourly | -4.4 | 6.7 | 20.0 | 7.8 | 9.2 | 3.4 |
Real Hourly Comp. | -9.1 | 5.3 | 24.4 | 7.4 | 7.9 | 1.2 |
Unit Labor Costs | -8.9 | 2.5 | 8.5 | 4.8 | 9.6 | 2.5 |
Unit Nonlabor Payments | 26.8 | -1.6 | -18.6 | -6.7 | -9.8 | 0.2 |
Implicit Price Deflator | 4.4 | 0.7 | -3.6 | -0.2 | 0.8 | 1.5 |
Notes: SAAE: seasonally adjusted annual equivalent; Comp.: compensation; YoY: Quarter on Same Quarter Year Earlier
The analysis by Kydland (https://www.nobelprize.org/prizes/economic-sciences/2004/kydland/biographical/) and Prescott (https://www.nobelprize.org/prizes/economic-sciences/2004/prescott/biographical/) (1977, 447-80, equation 5) uses the “expectation augmented” Phillips curve with the natural rate of unemployment of Friedman (1968) and Phelps (1968), which in the notation of Barro and Gordon (1983, 592, equation 1) is:
Ut = Unt – α(πt – πe) α > 0 (1)
Where Ut is the rate of unemployment at current time t, Unt is the natural rate of unemployment, πt is the current rate of inflation and πe is the expected rate of inflation by economic agents based on current information. Equation (1) expresses unemployment net of the natural rate of unemployment as a decreasing function of the gap between actual and expected rates of inflation. The system is completed by a social objective function, W, depending on inflation, π, and unemployment, U:
W = W(πt, Ut) (2)
The policymaker maximizes the preferences of the public, (2), subject to the constraint of the tradeoff of inflation and unemployment, (1). The total differential of W set equal to zero provides an indifference map in the Cartesian plane with ordered pairs (πt, Ut - Un) such that the consistent equilibrium is found at the tangency of an indifference curve and the Phillips curve in (1). The indifference curves are concave to the origin. The consistent policy is not optimal. Policymakers without discretionary powers following a rule of price stability would attain equilibrium with unemployment not higher than with the consistent policy. The optimal outcome is obtained by the rule of price stability, or zero inflation, and no more unemployment than under the consistent policy with nonzero inflation and the same unemployment. Taylor (1998LB) attributes the sustained boom of the US economy after the stagflation of the 1970s to following a monetary policy rule instead of discretion (see Taylor 1993, 1999). Professor John B. Taylor (2014Jul15, 2014Jun26) building on advanced research (Taylor 2007, 2008Nov, 2009, 2012FP, 2012Mar27, 2012Mar28, 2012JMCB, 2015, 2012 Oct 25; 2013Oct28, 2014 Jan01, 2014Jan3, 2014Jun26, 2014Jul15, 2015, 2016Dec7, 2016Dec20 http://www.johnbtaylor.com/) finds that a monetary policy rule would function best in promoting an environment of low inflation and strong economic growth with stability of financial markets. There is strong case for using rules instead of discretionary authorities in monetary policy (http://cmpassocregulationblog.blogspot.com/2017/01/rules-versus-discretionary-authorities.html and earlier http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html). It is not uncommon for effects of regulation differing from those intended by policy. Professors Edward C. Prescott and Lee E. Ohanian (2014Feb), writing on “US productivity growth has taken a dive,” on Feb 3, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702303942404579362462611843696?KEYWORDS=Prescott), argue that impressive productivity growth over the long-term constructed US prosperity and wellbeing. Prescott and Ohanian (2014Feb) measure US productivity growth at 2.5 percent per year since 1948. Average US productivity growth has been only 1.1 percent since 2011. Prescott and Ohanian (2014Feb) argue that living standards in the US increased at 28 percent in a decade but with current slow growth of productivity will only increase 12 percent by 2024. There may be collateral effects on productivity growth from policy design similar to those in Kydland and Prescott (1977). Professor Edward P. Lazear (2017Feb27), writing in the Wall Street Journal, on Feb 27, 2017 (https://www.wsj.com/articles/how-trump-can-hit-3-growthmaybe-1488239746), finds that productivity growth was 7 percent between 2009 and 2016 at annual equivalent 1 percent. Lazear measures productivity growth at 2.3 percent per year from 2001 to 2008. Herkenhoff, Ohanian and Prescott (2017) and Ohanian and Prescott (2017Dec) analyze how restriction of land use by states in the United States have been depressing economic activity. Professor Edmund S. Phelps (https://www.nobelprize.org/prizes/economic-sciences/2006/phelps/auto-biography/) argues that there is failed analysis that fiscal stimulus in the form of higher government expenditures and tax reductions caused the recovery of the economy to normal levels by 2017 (Phelps, Edmund S. 2018. The fantasy of fiscal stimulus. The Wall Street Journal Oct 29, 2018 https://www.wsj.com/articles/the-fantasy-of-fiscal-stimulus-1540852299?mod=searchresults&page=1&pos=2). The evidence analyzed by Phelps leads to the conclusion that countries with disorderly government finance grew less rapidly than those with sounder fiscal performance. Phelps concludes convincingly that “there is a strong relationship between the speed of recovery and a proxy of its dynamism—the long-term growth rate of total factor productivity from 1990 to 2007. Some countries have preexisting social institutions and cultural capital that enables them to bounce back from an economic downturn. Much credit of the U.S.’s relatively speedy recovery is owed to this country’s endemic culture of innovation and enterprise.” Professor Edward P. Lazear, writing on “Mind the productivity gap to reduce inequality,” published in the Wall Street Journal on May 6, 2019 (https://www.wsj.com/articles/mind-the-productivity-gap-to-reduce-inequality-11557181134?mod=searchresults&page=1&pos=1), analyzes the causes of the growing differential of wages between the income of the 90th percentile and the 50th percentile in terms of technological change. The improvement of the lower half of wage earners would consist of increasing their skills. Professors John F. Cogan and John B. Taylor, writing in the Wall Street Journal on Oct 6, 2020, measure productivity growth increasing from 0.8 percent per year in 2013-2016 to 1.5 percent per year in 2016-2019 because of deregulation and market-oriented policies. The Bureau of Labor Statistics important report on productivity and costs released Mar 5, 2020 (https://www.bls.gov/lpc/) supports the argument of decline of productivity growth in the US analyzed by Prescott and Ohanian (2014Feb), Lazear (2017Feb27), Phelps (2018) and Cogan and Taylor (2020Oct6). Table II-2 provides the annual percentage changes of productivity, real hourly compensation and unit labor costs for the entire economic cycle from 2007 to 2019. The estimates incorporate the yearly revision of the US national accounts (https://www.bea.gov/information-updates-national-income-and-product-accounts) and the comprehensive revisions since 1929 (https://apps.bea.gov/national/pdf/2018-ComprehensiveUpdate-Results.pdf). The data confirm the argument of Prescott and Ohanian (2014Feb), Lazear (2017Feb27) and Cogan and Taylor (2020Oct6): productivity increased cumulatively 8.8 percent from 2011 to 2019 at the average annual rate of 0.9 percent. Confirming measurement by Cogan and Taylor (2020Oct6), productivity increased at average 0.8 percent from 2013 to 2016 and at 1.4 percent from 2017 to 2019, using revised data. Average productivity growth for the entire economic cycle from 2007 to 2019 is only 1.4 percent. The argument by Prescott and Ohanian (2014Feb) is proper in choosing the tail of the business cycle because the increase in productivity in 2009 of 3.6 percent and 3.4 percent in 2010 consisted of reducing labor hours.
Table II-2, US, Revised Nonfarm Business Sector Productivity and Costs Annual Average, ∆% Annual Average
2017 ∆% | 2018 ∆% | 2019 ∆% | ||||
Productivity | 1.2 | 1.4 | 1.7 | |||
Real Hourly Compensation | 1.3 | 0.9 | 1.8 | |||
Unit Labor Costs | 2.2 | 1.9 | 1.9 | |||
2016 ∆% | 2015 ∆% | 2014 ∆% | 2013 ∆% | 2012 ∆% | 2011 ∆% | |
Productivity | 0.3 | 1.6 | 0.9 | 0.5 | 0.9 | 0.0 |
Real Hourly Compensation | -0.2 | 3.0 | 1.1 | -0.2 | 0.5 | -0.9 |
Unit Labor Costs | 0.7 | 1.6 | 1.9 | 0.8 | 1.8 | 2.2 |
2010 ∆% | 2009 ∆% | 2008 ∆% | 2007∆% | |
Productivity | 3.4 | 3.6 | 1.1 | 1.7 |
Real Hourly Compensation | 0.2 | 1.3 | -0.9 | 1.5 |
Unit Labor Costs | -1.5 | -2.5 | 1.7 | 2.6 |
Source: US Bureau of Labor Statistics
Table II-3, US, Nonfarm Business Output per Productivity jumped in the recovery after the recession from Mar IQ2001 to Nov IVQ2001 (https://www.nber.org/cycles.html) Table II-3 provides quarter on quarter and annual percentage changes in nonfarm business output per hour, or productivity, from 1999 to 2020. The annual average jumped from 2.7 percent in 2001 to 4.3 percent in 2002. Nonfarm business productivity increased at the SAAE rate of 9.0 percent in the first quarter after the recession in IQ2002. Productivity increases decline later in the expansion period. Productivity increases were mediocre during the recession from Dec IVQ2007 to Jun IIIQ2009 (https://www.nber.org/cycles.html) and increased during the first phase of expansion from IIQ2009 to IQ2010, trended lower and collapsed in 2011 and 2012 with sporadic jumps and declines. Productivity increased at 3.1 percent in IVQ2013 and contracted at 3.9 percent in IQ2014. Productivity increased at 4.2 percent in IIQ2014 and at 3.9 percent in IIIQ2014. Productivity contracted at 1.9 percent in IVQ2014 and increased at 3.7 percent in IQ2015. Productivity grew at 1.5 percent in IIQ2015 and increased at 1.1 percent in IIIQ2015. Productivity contracted at 2.2 percent in IVQ2015 and increased at 0.9 percent in IQ2016. Productivity decreased at 0.1 percent in IIQ2016 and expanded at 1.2 percent in IIIQ2016. Productivity grew at 2.5 percent in IVQ2016 and increased at 1.0 percent in IQ2017. Productivity decreased at 0.1 percent in IIQ2017 and increased at 2.5 percent in IIIQ2017. Productivity increased at 1.3 percent in IVQ2017 and increased at 2.3 percent in IQ2018. Productivity increased at 1.1 percent in IIQ2018 and increased at 0.5 percent in IIIQ2018. Productivity increased at 0.8 percent in IVQ2018. Productivity increased at 3.7 percent in IQ2019. Productivity increased at 2.0 percent in IIQ2019 and increased at 0.3 percent in IIIQ2019. Productivity increased at 1.6 percent in IVQ2019. Productivity decreased at 0.3 percent in IQ2020, increasing at 10.6 percent in IIQ2020 in the global recession, with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event. Productivity increased at 4.9 percent in IIIQ2020.
Table II-3, US, Nonfarm Business Output per Hour, Percent Change from Prior Quarter at Annual Rate, 1999-2020
Year | Qtr1 | Qtr2 | Qtr3 | Qtr4 | Annual |
1999 | 5.4 | 1.1 | 3.8 | 6.3 | 3.8 |
2000 | -0.6 | 8.4 | -0.3 | 4.4 | 3.3 |
2001 | -1.8 | 7.5 | 1.6 | 5.2 | 2.7 |
2002 | 9.0 | 0.5 | 3.1 | -0.2 | 4.3 |
2003 | 4.3 | 5.1 | 9.3 | 4.0 | 3.8 |
2004 | -1.4 | 3.8 | 1.8 | 1.9 | 2.9 |
2005 | 4.6 | -1.0 | 3.2 | 0.3 | 2.2 |
2006 | 2.9 | -0.3 | -1.2 | 3.4 | 1.1 |
2007 | 1.1 | 1.7 | 4.0 | 3.2 | 1.7 |
2008 | -3.1 | 4.2 | 1.2 | -2.7 | 1.1 |
2009 | 3.9 | 8.5 | 6.1 | 5.7 | 3.6 |
2010 | 2.0 | 1.0 | 2.2 | 1.4 | 3.4 |
2011 | -2.8 | 0.8 | -1.5 | 2.6 | 0.0 |
2012 | 1.5 | 1.9 | -0.9 | -1.4 | 0.9 |
2013 | 2.4 | -1.4 | 1.9 | 3.1 | 0.5 |
2014 | -3.9 | 4.2 | 3.9 | -1.9 | 0.9 |
2015 | 3.7 | 1.5 | 1.1 | -2.2 | 1.6 |
2016 | 0.9 | -0.1 | 1.2 | 2.5 | 0.3 |
2017 | 1.0 | -0.1 | 2.5 | 1.3 | 1.2 |
2018 | 2.3 | 1.1 | 0.5 | 0.8 | 1.4 |
2019 | 3.7 | 2.0 | 0.3 | 1.6 | 1.7 |
2020 | -0.3 | 10.6 | 4.9 |
Source: US Bureau of Labor Statistics
Chart II-1 of the Bureau of Labor Statistics (BLS) provides SAAE rates of nonfarm business productivity from 1999 to 2020. There is a clear pattern in both episodes of economic cycles in 2001 and 2007 of rapid expansion of productivity in the transition from contraction to expansion followed by more subdued productivity expansion. Part of the explanation is the reduction in labor utilization resulting from adjustment of business to the sudden shock of collapse of revenue. Productivity rose briefly in the expansion after 2009 but then collapsed and moved to negative change with some positive changes recently at lower rates. Contractions in the cycle from 2007 to 2019 have been more frequent and sharper. Productivity increased in 2020 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 as hours worked collapsed.
Chart II-1, US, Nonfarm Business Output per Hour, Percent Change from Prior Quarter at Annual Rate, 1999-2020
Source: US Bureau of Labor Statistics: http://www.bls.gov/lpc/
Percentage changes from prior quarter at SAAE rates and annual average percentage changes of nonfarm business unit labor costs are provided in Table II-4. Unit labor costs fell during the contractions with continuing negative percentage changes in the early phases of the recovery. Weak labor markets partly explain the decline in unit labor costs. As the economy moves toward full employment, labor markets tighten with increase in unit labor costs. The expansion beginning in IIIQ2009 has been characterized by high unemployment and underemployment. Table II-4 shows continuing subdued increases in unit labor costs in 2011 but with increase at 8.2 percent in IQ2012 followed by increase at 0.3 percent in IIQ2012, increase at 1.2 percent in IIIQ2012 and increase at 12.6 percent in IVQ2012. Unit labor costs decreased at 7.8 percent in IQ2013 and increased at 4.4 percent in IIQ2013. Unit labor costs decreased at 2.9 percent in IIIQ2013 and decreased at 0.2 percent in IVQ2013. Unit labor costs increased at 12.4 percent in IQ2014 and at minus 5.7 percent in IIQ2014. Unit labor costs decreased at 1.1 percent in IIIQ2014 and increased at 6.2 percent in IVQ2014. Unit labor costs increased at 1.6 percent in IQ2015 and increased at 1.7 percent in IIQ2015. Unit labor costs increased at 0.5 percent in IIIQ2015 and increased at 2.0 percent in IVQ2015. Unit labor costs decreased at 0.9 percent in IQ2016 and increased at 1.3 percent in IIQ2016. Unit labor costs increased at 0.5 percent in IIIQ2016 and increased at 1.7 percent in IVQ2016. Unit labor costs increased at 2.9 percent in IQ2017 and increased at 2.5 percent in IIQ2017. United labor costs increased at 2.7 percent in IIIQ2017 and increased at 4.1 percent in IVQ2017. Unit labor costs changed at 0.0 percent in IQ2018 and increased at 0.2 percent in IIQ2018. Unit labor costs increased at 4.5 percent in IIIQ2018 and increased at 1.0 percent in IVQ2018. Unit labor costs increased at 4.8 percent in IQ2019 and decreased at 0.6 percent in IIQ2019. Unit labor costs decreased at 0.4 percent in IIIQ2019 and increased at 1.7 percent in IVQ2019. Unit labor costs increased at 9.6 percent in IQ2020 and increased at 8.5 percent in IIQ2020. Unit labor costs decreased at 8.9 percent in IIIQ2020.
Table II-4, US, Nonfarm Business Unit Labor Costs, Percent Change from Prior Quarter at Annual Rate 1999-2020
Year | Qtr1 | Qtr2 | Qtr3 | Qtr4 | Annual |
1999 | 1.8 | 0.6 | -0.2 | 1.9 | 0.8 |
2000 | 15.6 | -6.8 | 8.3 | -2.1 | 3.6 |
2001 | 11.3 | -5.5 | -1.1 | -1.4 | 1.6 |
2002 | -6.5 | 3.0 | -1.0 | 1.3 | -1.9 |
2003 | -1.7 | 1.9 | -3.0 | 1.7 | -0.1 |
2004 | 0.7 | 4.0 | 5.4 | -0.2 | 1.6 |
2005 | -1.7 | 3.4 | 1.8 | 2.2 | 1.4 |
2006 | 5.2 | 0.6 | 1.9 | 3.7 | 2.7 |
2007 | 8.9 | -1.9 | -2.3 | 1.3 | 2.6 |
2008 | 7.4 | -3.4 | 2.6 | 6.9 | 1.7 |
2009 | -13.4 | 1.7 | -3.6 | -3.1 | -2.5 |
2010 | -4.4 | 3.3 | -0.5 | 0.8 | -1.5 |
2011 | 10.5 | -3.4 | 4.5 | -7.6 | 2.2 |
2012 | 8.2 | 0.3 | 1.2 | 12.6 | 1.8 |
2013 | -7.8 | 4.4 | -2.9 | -0.2 | 0.8 |
2014 | 12.4 | -5.7 | -1.1 | 6.2 | 1.9 |
2015 | 1.6 | 1.7 | 0.5 | 2.0 | 1.6 |
2016 | -0.9 | 1.3 | 0.5 | 1.7 | 0.7 |
2017 | 2.9 | 2.5 | 2.7 | 4.1 | 2.2 |
2018 | 0.0 | 0.2 | 4.5 | 1.0 | 1.9 |
2019 | 4.8 | -0.6 | -0.4 | 1.7 | 1.9 |
2020 | 9.6 | 8.5 | -8.9 |
Source: US Bureau of Labor Statistics
Chart II-2 provides change of unit labor costs at SAAE from 1999 to 2020. There are multiple oscillations recently with negative changes alternating with positive changes. There is sharp contraction in 2020 in the global recession, with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event.
Chart II-2, US, Nonfarm Business Unit Labor Costs, Percent Change from Prior Quarter at Annual Rate 1999-2020
Source: US Bureau of Labor Statistics: https://www.bls.gov/lpc/
Table II-5 provides percentage change from prior quarter at annual rates for nonfarm business real hourly worker compensation. The expansion after the contraction of 2001 was followed by strong recovery of real hourly compensation. Real hourly compensation increased at the rate of 3.0 percent in IQ2011 but fell at annual rates of 6.9 percent in IIQ2011 and 7.0 percent in IVQ2011. Real hourly compensation increased at 7.2 percent in IQ2012, increasing at 1.3 percent in IIQ2012, declining at 1.6 percent in IIIQ2012 and increasing at 8.2 percent in IVQ2012. Real hourly compensation fell at 0.9 percent in 2011 and increased at 0.5 percent in 2012. Real hourly compensation fell at 7.2 percent in IQ2013 and increased at 3.3 percent in IIQ2013, falling at 3.2 percent in IIIQ2013. Real hourly compensation increased at 1.4 percent in IVQ2013 and at 5.2 percent in IQ2014. Real hourly compensation decreased at 3.9 percent in IIQ2014. Real hourly compensation increased at 1.6 percent in IIIQ2014. The annual rate of increase of real hourly compensation for 2013 is minus 0.2 percent. Real hourly compensation increased at 5.3 percent in IVQ2014. The annual rate of increase of real hourly compensation in 2014 is 1.1 percent. Real hourly compensation increased at 8.0 percent in IQ2015 and increased at 0.5 percent in IIQ2015. Real hourly compensation increased at 0.1 percent in IIIQ2015 and decreased at 0.3 percent in IVQ2015. Real hourly compensation increased at 3.0 percent in 2015. Real hourly compensation increased at 0.2 percent in IQ2016 and decreased at 1.7 percent in IIQ2016. Real hourly compensation decreased at 0.2 percent in IIIQ2016 and increased at 1.7 percent in IVQ2016. Real hourly compensation decreased 0.2 percent in 2016. Real hourly compensation increased at 1.0 percent in IQ2017 and increased at 2.0 percent in IIQ2017. Real hourly compensation increased at 3.0 percent in IIIQ2017. Real hourly compensation increased at 2.3 percent in IVQ2017. Real hourly compensation increased 1.3 percent in 2017. Real hourly compensation decreased at 1.0 percent in IQ2018 and decreased at 0.9 percent in IIQ2018. Real hourly compensation increased at 2.9 percent in IIIQ2018 and increased at 0.5 percent in IVQ2018. Real hourly compensation increased 0.9 percent in 2018. Real hourly compensation increased at 7.7 percent in IQ2019 and decreased at 1.6 percent in IIQ2019. Real hourly compensation decreased at 2.0 percent in IIIQ2019, decreasing at 0.9 percent in IVQ2019. Real hourly compensation increased 1.8 percent in 2019. Real hourly compensation increased at 7.9 percent in IQ2020 and increased at 24.4 percent in IIQ2020. Real hourly compensation decreased at 9.1 percent in IIIQ2020.
Table II-5, Nonfarm Business Real Hourly Compensation, Percent Change from Prior Quarter at Annual Rate, 1999-2020
Year | Qtr1 | Qtr2 | Qtr3 | Qtr4 | Annual |
1999 | 5.8 | -1.4 | 0.5 | 5.0 | 2.5 |
2000 | 10.4 | -2.1 | 4.1 | -0.5 | 3.5 |
2001 | 5.2 | -1.3 | -0.5 | 4.2 | 1.5 |
2002 | 0.5 | 0.3 | -0.1 | -1.3 | 0.7 |
2003 | -1.6 | 7.8 | 3.0 | 4.1 | 1.4 |
2004 | -4.0 | 4.7 | 4.6 | -2.6 | 1.8 |
2005 | 0.8 | -0.4 | -1.0 | -1.3 | 0.3 |
2006 | 6.0 | -3.3 | -3.0 | 9.0 | 0.6 |
2007 | 6.0 | -4.6 | -1.0 | -0.4 | 1.5 |
2008 | -0.4 | -4.4 | -2.3 | 14.2 | -0.9 |
2009 | -7.5 | 8.0 | -1.1 | -0.7 | 1.3 |
2010 | -3.1 | 4.4 | 0.4 | -1.0 | 0.2 |
2011 | 3.0 | -6.9 | 0.3 | -7.0 | -0.9 |
2012 | 7.2 | 1.3 | -1.6 | 8.2 | 0.5 |
2013 | -7.2 | 3.3 | -3.2 | 1.4 | -0.2 |
2014 | 5.2 | -3.9 | 1.6 | 5.3 | 1.1 |
2015 | 8.0 | 0.5 | 0.1 | -0.3 | 3.0 |
2016 | 0.2 | -1.7 | -0.2 | 1.7 | -0.2 |
2017 | 1.0 | 2.0 | 3.0 | 2.3 | 1.3 |
2018 | -1.0 | -0.9 | 2.9 | 0.5 | 0.9 |
2019 | 7.7 | -1.6 | -2.0 | 0.9 | 1.8 |
2020 | 7.9 | 24.4 | -9.1 |
Source: US Bureau of Labor Statistics
Chart II-3 provides percentage change from prior quarter at annual rate of nonfarm business real hourly compensation. There have been multiple negative percentage quarterly changes in the current cycle since IVQ2007. There is meager growth recently. There is sharp increase followed by sharp decrease in 2020 in the global recession, with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event.
Chart II-3, US, Nonfarm Business Real Hourly Compensation, Percent Change from Prior Quarter at Annual Rate 1999-2020
Source: US Bureau of Labor Statistics https://www.bls.gov/lpc/
Chart II-4 provides percentage change of nonfarm business output per hour in a quarter relative to the same quarter a year earlier. As in most series of real output, productivity increased sharply in 2010 but the momentum was lost after 2011 as with the rest of the real economy. There are more negative yearly changes during the current cycle than in cycle after 1999. There is sharp increase in 2020 in the global recession, with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19 event.
Chart II-4, US, Nonfarm Business Output per Hour, Percent Change from Same Quarter a Year Earlier 1999-2020
Source: US Bureau of Labor Statistics: https://www.bls.gov/lpc/
Chart II-5 provides percentage changes of nonfarm business unit labor costs relative to the same quarter a year earlier. Softening of labor markets caused relatively high yearly percentage changes in the recession of 2001 repeated in the recession in 2009. Recovery was strong in 2010 but then weakened.
Chart II-5, US, Nonfarm Business Unit Labor Costs, Percent Change from Same Quarter a Year Earlier 1999-2020
Source: US Bureau of Labor Statistics: https://www.bls.gov/lpc/
Chart II-6 provides percentage changes of real hourly compensation in a month relative to the same month a year earlier. There is significant volatility in part because of recurring world inflation waves originating in carry trades from artificially low interest rates.
Chart II-6, US, Nonfarm Business Real Hourly Compensation, Percent Change from Same Quarter a Year Earlier 1999-2020
2012=100
Source: US Bureau of Labor Statistics: https://www.bls.gov/lpc/
In the analysis of Hansen (1939, 3) of secular stagnation, economic progress consists of growth of real income per person driven by growth of productivity. The “constituent elements” of economic progress are “(a) inventions, (b) the discovery and development of new territory and new resources, and (c) the growth of population” (Hansen 1939, 3). Secular stagnation originates in decline of population growth and discouragement of inventions. According to Hansen (1939, 2), US population grew by 16 million in the 1920s but grew by one half or about 8 million in the 1930s with forecasts at the time of Hansen’s writing in 1938 of growth of around 5.3 million in the 1940s. Hansen (1939, 2) characterized demography in the US as “a drastic decline in the rate of population growth.” Hansen’s plea was to adapt economic policy to stagnation of population in ensuring full employment. In the analysis of Hansen (1939, 8), population caused half of the growth of US GDP per year. Growth of output per person in the US and Europe was caused by “changes in techniques and to the exploitation of new natural resources.” In this analysis, population caused 60 percent of the growth of capital formation in the US. Declining population growth would reduce growth of capital formation. Residential construction provided an important share of growth of capital formation. Hansen (1939, 12) argues that market power of imperfect competition discourages innovation with prolonged use of obsolete capital equipment. Trade unions would oppose labor-savings innovations. The combination of stagnating and aging population with reduced innovation caused secular stagnation. Hansen (1939, 12) concludes that there is role for public investments to compensate for lack of dynamism of private investment but with tough tax/debt issues.
The current application of Hansen’s (1938, 1939, 1941) proposition argues that secular stagnation occurs because full employment equilibrium can be attained only with negative real interest rates between minus 2 and minus 3 percent. Professor Lawrence H. Summers (2013Nov8) finds that “a set of older ideas that went under the phrase secular stagnation are not profoundly important in understanding Japan’s experience in the 1990s and may not be without relevance to America’s experience today” (emphasis added). Summers (2013Nov8) argues there could be an explanation in “that the short-term real interest rate that was consistent with full employment had fallen to -2% or -3% sometime in the middle of the last decade. Then, even with artificial stimulus to demand coming from all this financial imprudence, you wouldn’t see any excess demand. And even with a relative resumption of normal credit conditions, you’d have a lot of difficulty getting back to full employment.” The US economy could be in a situation where negative real rates of interest with fed funds rates close to zero as determined by the Federal Open Market Committee (FOMC) do not move the economy to full employment or full utilization of productive resources. Summers (2013Oct8) finds need of new thinking on “how we manage an economy in which the zero nominal interest rates is a chronic and systemic inhibitor of economy activity holding our economies back to their potential.”
Former US Treasury Secretary Robert Rubin (2014Jan8) finds three major risks in prolonged unconventional monetary policy of zero interest rates and quantitative easing: (1) incentive of delaying action by political leaders; (2) “financial moral hazard” in inducing excessive exposures pursuing higher yields of risker credit classes; and (3) major risks in exiting unconventional policy. Rubin (2014Jan8) proposes reduction of deficits by structural reforms that could promote recovery by improving confidence of business attained with sound fiscal discipline.
Professor John B. Taylor (2014Jan01, 2014Jan3) provides clear thought on the lack of relevance of Hansen’s contention of secular stagnation to current economic conditions. The application of secular stagnation argues that the economy of the US has attained full-employment equilibrium since around 2000 only with negative real rates of interest of minus 2 to minus 3 percent. At low levels of inflation, the so-called full-employment equilibrium of negative interest rates of minus 2 to minus 3 percent cannot be attained and the economy stagnates. Taylor (2014Jan01) analyzes multiple contradictions with current reality in this application of the theory of secular stagnation:
- Secular stagnation would predict idle capacity, in particular in residential investment when fed fund rates were fixed at 1 percent from Jun 2003 to Jun 2004. Taylor (2014Jan01) finds unemployment at 4.4 percent with house prices jumping 7 percent from 2002 to 2003 and 14 percent from 2004 to 2005 before dropping from 2006 to 2007. GDP prices doubled from 1.7 percent to 3.4 percent when interest rates were low from 2003 to 2005.
- Taylor (2014Jan01, 2014Jan3) finds another contradiction in the application of secular stagnation based on low interest rates because of savings glut and lack of investment opportunities. Taylor (2009) shows that there was no savings glut. The savings rate of the US in the past decade is significantly lower than in the 1980s.
- Taylor (2014Jan01, 2014Jan3) finds another contradiction in the low ratio of investment to GDP currently and reduced investment and hiring by US business firms.
- Taylor (2014Jan01, 2014Jan3) argues that the financial crisis and global recession were caused by weak implementation of existing regulation and departure from rules-based policies.
Taylor (2014Jan01, 2014Jan3) argues that the recovery from the global recession was constrained by a change in the regime of regulation and fiscal/monetary policies.
The analysis by Kydland (https://www.nobelprize.org/prizes/economic-sciences/2004/kydland/biographical/) and Prescott (https://www.nobelprize.org/prizes/economic-sciences/2004/prescott/biographical/) (1977, 447-80, equation 5) uses the “expectation augmented” Phillips curve with the natural rate of unemployment of Friedman (1968) and Phelps (1968), which in the notation of Barro and Gordon (1983, 592, equation 1) is:
Ut = Unt – α(πt – πe) α > 0 (1)
Where Ut is the rate of unemployment at current time t, Unt is the natural rate of unemployment, πt is the current rate of inflation and πe is the expected rate of inflation by economic agents based on current information. Equation (1) expresses unemployment net of the natural rate of unemployment as a decreasing function of the gap between actual and expected rates of inflation. The system is completed by a social objective function, W, depending on inflation, π, and unemployment, U:
W = W(πt, Ut) (2)
The policymaker maximizes the preferences of the public, (2), subject to the constraint of the tradeoff of inflation and unemployment, (1). The total differential of W set equal to zero provides an indifference map in the Cartesian plane with ordered pairs (πt, Ut - Un) such that the consistent equilibrium is found at the tangency of an indifference curve and the Phillips curve in (1). The indifference curves are concave to the origin. The consistent policy is not optimal. Policymakers without discretionary powers following a rule of price stability would attain equilibrium with unemployment not higher than with the consistent policy. The optimal outcome is obtained by the rule of price stability, or zero inflation, and no more unemployment than under the consistent policy with nonzero inflation and the same unemployment. Taylor (1998LB) attributes the sustained boom of the US economy after the stagflation of the 1970s to following a monetary policy rule instead of discretion (see Taylor 1993, 1999). Professor John B. Taylor (2014Jul15, 2014Jun26) building on advanced research (Taylor 2007, 2008Nov, 2009, 2012FP, 2012Mar27, 2012Mar28, 2012JMCB, 2015, 2012 Oct 25; 2013Oct28, 2014 Jan01, 2014Jan3, 2014Jun26, 2014Jul15, 2015, 2016Dec7, 2016Dec20 http://www.johnbtaylor.com/) finds that a monetary policy rule would function best in promoting an environment of low inflation and strong economic growth with stability of financial markets. There is strong case for using rules instead of discretionary authorities in monetary policy (http://cmpassocregulationblog.blogspot.com/2017/01/rules-versus-discretionary-authorities.html and earlier http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html). It is not uncommon for effects of regulation differing from those intended by policy. Professors Edward C. Prescott and Lee E. Ohanian (2014Feb), writing on “US productivity growth has taken a dive,” on Feb 3, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702303942404579362462611843696?KEYWORDS=Prescott), argue that impressive productivity growth over the long-term constructed US prosperity and wellbeing. Prescott and Ohanian (2014Feb) measure US productivity growth at 2.5 percent per year since 1948. Average US productivity growth has been only 1.1 percent since 2011. Prescott and Ohanian (2014Feb) argue that living standards in the US increased at 28 percent in a decade but with current slow growth of productivity will only increase 12 percent by 2024. There may be collateral effects on productivity growth from policy design similar to those in Kydland and Prescott (1977). Professor Edward P. Lazear (2017Feb27), writing in the Wall Street Journal, on Feb 27, 2017 (https://www.wsj.com/articles/how-trump-can-hit-3-growthmaybe-1488239746), finds that productivity growth was 7 percent between 2009 and 2016 at annual equivalent 1 percent. Lazear measures productivity growth at 2.3 percent per year from 2001 to 2008. Herkenhoff, Ohanian and Prescott (2017) and Ohanian and Prescott (2017Dec) analyze how restriction of land use by states in the United States have been depressing economic activity. Professor Edmund S. Phelps (https://www.nobelprize.org/prizes/economic-sciences/2006/phelps/auto-biography/) argues that there is failed analysis that fiscal stimulus in the form of higher government expenditures and tax reductions caused the recovery of the economy to normal levels by 2017 (Phelps, Edmund S. 2018. The fantasy of fiscal stimulus. The Wall Street Journal Oct 29, 2018 https://www.wsj.com/articles/the-fantasy-of-fiscal-stimulus-1540852299?mod=searchresults&page=1&pos=2). The evidence analyzed by Phelps leads to the conclusion that countries with disorderly government finance grew less rapidly than those with sounder fiscal performance. Phelps concludes convincingly that “there is a strong relationship between the speed of recovery and a proxy of its dynamism—the long-term growth rate of total factor productivity from 1990 to 2007. Some countries have preexisting social institutions and cultural capital that enables them to bounce back from an economic downturn. Much credit of the U.S.’s relatively speedy recovery is owed to this country’s endemic culture of innovation and enterprise.” Professor Edward P. Lazear, writing on “Mind the productivity gap to reduce inequality,” published in the Wall Street Journal on May 6, 2019 (https://www.wsj.com/articles/mind-the-productivity-gap-to-reduce-inequality-11557181134?mod=searchresults&page=1&pos=1), analyzes the causes of the growing differential of wages between the income of the 90th percentile and the 50th percentile in terms of technological change. The improvement of the lower half of wage earners would consist of increasing their skills. Professors John F. Cogan and John B. Taylor, writing in the Wall Street Journal on Oct 6, 2020, measure productivity growth increasing from 0.8 percent per year in 2013-2016 to 1.5 percent per year in 2016-2019 because of deregulation and market-oriented policies. The Bureau of Labor Statistics important report on productivity and costs released Mar 5, 2020 (https://www.bls.gov/lpc/) supports the argument of decline of productivity growth in the US analyzed by Prescott and Ohanian (2014Feb), Lazear (2017Feb27), Phelps (2018) and Cogan and Taylor (2020Oct6). Table II-2 provides the annual percentage changes of productivity, real hourly compensation and unit labor costs for the entire economic cycle from 2007 to 2019. The estimates incorporate the yearly revision of the US national accounts (https://www.bea.gov/information-updates-national-income-and-product-accounts) and the comprehensive revisions since 1929 (https://apps.bea.gov/national/pdf/2018-ComprehensiveUpdate-Results.pdf). The data confirm the argument of Prescott and Ohanian (2014Feb), Lazear (2017Feb27) and Cogan and Taylor (2020Oct6): productivity increased cumulatively 8.8 percent from 2011 to 2019 at the average annual rate of 0.9 percent. Confirming measurement by Cogan and Taylor (2020Oct6), productivity increased at average 0.8 percent from 2013 to 2016 and at 1.4 percent from 2017 to 2019, using revised data. Average productivity growth for the entire economic cycle from 2007 to 2019 is only 1.4 percent. The argument by Prescott and Ohanian (2014Feb) is proper in choosing the tail of the business cycle because the increase in productivity in 2009 of 3.6 percent and 3.4 percent in 2010 consisted of reducing labor hours.
In revealing research, Edward P. Lazear and James R. Spletzer (2012JHJul22) use the wealth of data in the valuable database and resources of the Bureau of Labor Statistics (http://www.bls.gov/data/) in providing clear thought on the nature of the current labor market of the United States. The critical issue of analysis and policy currently is whether unemployment is structural or cyclical. Structural unemployment could occur because of (1) industrial and demographic shifts and (2) mismatches of skills and job vacancies in industries and locations. Consider the aggregate unemployment rate, Y, expressed in terms of share si of a demographic group in an industry i and unemployment rate yi of that demographic group (Lazear and Spletzer 2012JHJul22, 5-6):
Y = ∑isiyi (1)
This equation can be decomposed for analysis as (Lazear and Spletzer 2012JHJul22, 6):
∆Y = ∑i∆siy*i + ∑i∆yis*i (2)
The first term in (2) captures changes in the demographic and industrial composition of the economy ∆si multiplied by the average rate of unemployment y*i , or structural factors. The second term in (2) captures changes in the unemployment rate specific to a group, or ∆yi, multiplied by the average share of the group s*i, or cyclical factors. There are also mismatches in skills and locations relative to available job vacancies. A simple observation by Lazear and Spletzer (2012JHJul22) casts intuitive doubt on structural factors: the rate of unemployment jumped from 4.4 percent in the spring of 2007 to 10 percent in October 2009. By nature, structural factors should be permanent or occur over relative long periods. The revealing result of the exhaustive research of Lazear and Spletzer (2012JHJul22) is:
“The analysis in this paper and in others that we review do not provide any compelling evidence that there have been changes in the structure of the labor market that are capable of explaining the pattern of persistently high unemployment rates. The evidence points to primarily cyclic factors.”
The theory of secular stagnation cannot explain sudden collapse of the US economy and labor markets. The theory of secular stagnation departs from an aggregate production function in which output grows with the use of labor, capital and technology (see Pelaez and Pelaez, Globalization and the State, Vol. I (2008a), 11-6). Simon Kuznets (1971) analyzes modern economic growth in his Lecture in Memory of Alfred Nobel:
“The major breakthroughs in the advance of human knowledge, those that constituted dominant sources of sustained growth over long periods and spread to a substantial part of the world, may be termed epochal innovations. And the changing course of economic history can perhaps be subdivided into economic epochs, each identified by the epochal innovation with the distinctive characteristics of growth that it generated. Without considering the feasibility of identifying and dating such economic epochs, we may proceed on the working assumption that modern economic growth represents such a distinct epoch - growth dating back to the late eighteenth century and limited (except in significant partial effects) to economically developed countries. These countries, so classified because they have managed to take adequate advantage of the potential of modern technology, include most of Europe, the overseas offshoots of Western Europe, and Japan—barely one quarter of world population.”
Chart II-7 provides nonfarm-business labor productivity, measured by output per hour, from 1947 to 2020. The rate of productivity increase continued in the early part of the 2000s but then softened and fell during the global recession. The interruption of productivity increases occurred exclusively in the current business cycle. Lazear and Spletzer (2012JHJul22) find “primarily cyclic” factors in explaining the frustration of currently depressed labor markets in the United States. Stagnation of productivity is another cyclic event and not secular trend. The theory and application of secular stagnation to current US economic conditions is void of reality.
Chart II-7, US, Nonfarm Business Labor Productivity, Output per Hour, 1947-2020, Index 2012=100
Source: US Bureau of Labor Statistics: https://www.bls.gov/lpc/
Table II-6 expands Table II-2 providing more complete measurements of the Productivity and Cost research of the Bureau of Labor Statistics. The proper emphasis of Prescott and Ohanian (2014Feb) is on the low productivity increases from 2011 to 2019. Labor productivity increased 3.4 percent in 2010 and 3.6 percent in 2009. There is much stronger yet not sustained performance in 2010 with productivity growing 3.4 percent because of growth of output of 3.3 percent with decline of hours worked of 0.1 percent. Productivity growth of 3.6 percent in 2009 consists of decline of output by 3.9 percent while hours worked collapsed 7.2 percent, which is not a desirable route to progress. The expansion phase of the economic cycle concentrated in one year, 2010, with underperformance in the remainder of the expansion from 2011 to 2019 of productivity growth at average 0.9 percent per year.
Table II-6, US, Productivity and Costs, Annual Percentage Changes 2007-2019
2017 | 2018 | 2019 | |||
Productivity | 1.2 | 1.4 | 17 | ||
Output | 2.8 | 3.5 | 2.5 | ||
Hours Worked | 1.5 | 2.0 | 0.7 | ||
Employment | 1.6 | 1.9 | 1.2 | ||
Average Weekly Hours Worked | 0.0 | 0.1 | -0.5 | ||
Unit Labor Costs | 2.2 | 1.9 | 1.9 | ||
Hourly Compensation | 3.5 | 3.4 | 3.6 | ||
Consumer Price Inflation | 2.1 | 2.4 | 1.8 | ||
Real Hourly Compensation | 1.3 | 0.9 | 1.8 | ||
Non-labor Payments | 3.7 | 6.3 | 3.5 | ||
Output per Job | 1.2 | 1.6 | 1.2 | ||
2016 | 2015 | 2014 | 2013 | 2012 | |
Productivity | 0.3 | 1.6 | 0.9 | 0.5 | 0.9 |
Output | 1.8 | 3.7 | 3.2 | 2.2 | 3.1 |
Hours Worked | 1.5 | 2.1 | 2.3 | 1.7 | 2.3 |
Employment | 1.8 | 2.2 | 2.0 | 1.8 | 2.0 |
Average Weekly Hours Worked | -0.3 | -0.1 | 0.2 | -0.1 | 0.3 |
Unit Labor Costs | 0.7 | 1.6 | 1.9 | 0.8 | 1.8 |
Hourly Compensation | 1.1 | 3.1 | 2.8 | 1.3 | 2.7 |
Consumer Price Inflation | 1.3 | 0.1 | 1.6 | 1.5 | 2.1 |
Real Hourly Compensation | -0.2 | 3.0 | 1.1 | -0.2 | 0.5 |
Non-labor Payments | 3.2 | 3.3 | 4.8 | 4.6 | 5.2 |
Output per Job | 0.0 | 1.5 | 1.1 | 0.4 | 1.1 |
2011 | 2010 | 2009 | 2008 | 2007 | |
Productivity | 0.0 | 3.4 | 3.6 | 1.1 | 1.7 |
Output | 2.0 | 3.3 | -3.9 | -1.0 | 2.4 |
Hours Worked | 2.0 | -0.1 | -7.2 | -2.1 | 0.7 |
Employment | 1.6 | -1.2 | -5.7 | -1.4 | 0.9 |
Average Weekly Hours Worked | 0.4 | 1.1 | -1.6 | -0.7 | -0.2 |
Unit Labor Costs | 2.2 | -1.5 | -2.5 | 1.7 | 2.6 |
Hourly Compensation | 2.2 | 1.9 | 0.9 | 2.9 | 4.3 |
Consumer Price Inflation | 3.2 | 1.6 | -0.4 | 3.8 | 2.8 |
Real Hourly Compensation | -0.9 | 0.2 | 1.3 | -0.9 | 1.5 |
Non-labor Payments | 3.6 | 7.8 | 1.0 | 0.3 | 3.6 |
Output per Job | 0.4 | 4.5 | 1.9 | 0.4 | 1.5 |
Source: US Bureau of Labor Statistics https://www.bls.gov/lpc/
Productivity growth can bring about prosperity while productivity regression can jeopardize progress. Cobet and Wilson (2002) provide estimates of output per hour and unit labor costs in national currency and US dollars for the US, Japan and Germany from 1950 to 2000 (see Pelaez and Pelaez, The Global Recession Risk (2007), 137-44). The average yearly rate of productivity change from 1950 to 2000 was 2.9 percent in the US, 6.3 percent for Japan and 4.7 percent for Germany while unit labor costs in USD increased at 2.6 percent in the US, 4.7 percent in Japan and 4.3 percent in Germany. From 1995 to 2000, output per hour increased at the average yearly rate of 4.6 percent in the US, 3.9 percent in Japan and 2.6 percent in Germany while unit labor costs in USD fell at minus 0.7 percent in the US, 4.3 percent in Japan and 7.5 percent in Germany. There was increase in productivity growth in Japan and France within the G7 in the second half of the 1990s but significantly lower than the acceleration of 1.3 percentage points per year in the US. Table II-7 provides average growth rates of indicators in the research of productivity and growth of the US Bureau of Labor Statistics. There is dramatic decline of productivity growth from 2.1 percent per year on average from 1947 to 2019 to 1.4 percent per year on average in the whole cycle from 2007 to 2019. Productivity increased at the average rate of 2.3 percent from 1947 to 2007. There is profound drop in the average rate of output growth from 3.4 percent on average from 1947 to 2019 to 1.9 percent from 2007 to 2019. Output grew at 3.7 percent per year on average from 1947 to 2007. 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 1.8 percent on average in the cyclical expansion in the 45 quarters from IIIQ2009 to IIIQ2020 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 first estimate of GDP for IIIQ2020 (https://www.bea.gov/sites/default/files/2020-10/gdp3q20_adv.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.8 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/2020/11/us-gdp-growing-at-saar-331-percent-in.html earlier https://cmpassocregulationblog.blogspot.com/2020/10/dollar-carry-trades-induced-from-zero.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 IIIQ1992, 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, 3.7 percent from IQ1983 to IVQ1993, 3.7 percent from IQ1983 to IQ1994 and at 7.9 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2020/11/us-gdp-growing-at-saar-331-percent-in.html earlier https://cmpassocregulationblog.blogspot.com/2020/10/dollar-carry-trades-induced-from-zero.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 IIIQ2020 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 45.8 percent. GDP in IIIQ2020 would be $22,981.0 billion (in constant dollars of 2012) if the US had grown at trend, which is higher by $4397.0 billion than actual $18,584.0 billion. There are more than four trillion dollars of GDP less than at trend, explaining the 30.6 million unemployed or underemployed equivalent to actual unemployment/underemployment of 17.7 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/2020/11/increase-in-oct-2020-of-nonfarm-payroll.html and earlier https://cmpassocregulationblog.blogspot.com/2020/10/increasingvaluations-of-risk-financial.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/covid19/employment-situation-covid19-faq-october-2020.htm). US GDP in IIIQ2020 is 19.1 percent lower than at trend. US GDP grew from $15,762.0 billion in IVQ2007 in constant dollars to $18,584.0 billion in IIIQ2020 or 17.9 percent at the average annual equivalent rate of 1.3 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.0 percent per year from Oct 1919 to Oct 2020. 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 158.2586 in Oct 2020. The actual index NSA in Oct 2020 is 101.0760 which is 36.1 percent below trend. The underperformance of manufacturing in Mar-Aug 2020 originates partly in the earlier global recession augmented by the current global recession with output in the US reaching a high in Feb 2020 (https://www.nber.org/cycles.html), in the lockdown of economic activity in the COVID-19. Manufacturing grew at the average annual rate of 3.3 percent between Dec 1986 and Dec 2006. Growth at 3.3 percent per year would raise the NSA index of manufacturing output (SIC, Standard Industrial Classification) from 108.2987 in Dec 2007 to 164.2771 in Oct 2020. The actual index NSA in Oct 2020 is 101.0760, which is 38.5 percent below trend. Manufacturing output grew at average 1.8 percent between Dec 1986 and Oct 2020. Using trend growth of 1.8 percent per year, the index would increase to 136.1610 in Oct 2020. The output of manufacturing at 101.0760 in Oct 2020 is 25.8 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 102.4731 in Oct 2020 or 18.6 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 165.8852 in Oct 2020. The NAICS index at 102.4731 in Oct 2020 is 38.2 below trend. The NAICS manufacturing output index grew at 1.7 percent annual equivalent from Dec 1999 to Dec 2006. Growth at 1.7 percent would raise the NAICS manufacturing output index from 106.6777 in Dec 2007 to 132.4420 in Oct 2020. The NAICS index at 102.4731 in Oct 2020 is 22.6 percent below trend under this alternative calculation.
Table II-7, US, Productivity and Costs, Average Annual Percentage Changes 2007-2019, 1947-2007 and 1947-2019
Average Annual Percentage Rate 2007-2019 | Average Annual Percentage Rate 1947-2007 | Average Annual Percentage Rate 1947-2019 | |
Productivity | 1.4 | 2.3 | 2.1 |
Output | 1.9 | 3.7 | 3.4 |
Hours | 0.5 | 1.4 | 1.2 |
Employment | 0.6 | 1.6 | 1.5 |
Average Weekly Hours | -1.2* | -14.4* | -15.5* |
Hourly Compensation | 2.4 | 5.4 | 4.9 |
Consumer Price Inflation | 1.8 | 3.8 | 3.4 |
Real Hourly Compensation | 0.6 | 1.7 | 1.5 |
Unit Labor Costs | 1.0 | 3.0 | 2.7 |
Unit Non-Labor Payments | 2.0 | 3.5 | 3.2 |
Output per Job | 1.3 | 2.0 | 1.9 |
* Percentage Change
Source: US Bureau of Labor Statistics https://www.bls.gov/lpc/
Unit labor costs increased sharply during the Great Inflation from the late 1960s to 1981 as shown by sharper slope in Chart II-8. Unit labor costs continued to increase but at a lower rate because of cyclic factors and not because of imaginary secular stagnation.
Chart II-8, US, Nonfarm Business, Unit Labor Costs, 1947-2020, Index 2012=100
Source: US Bureau of Labor Statistics: https://www.bls.gov/lpc/
Real hourly compensation increased at relatively high rates after 1947 to the early 1970s but reached a plateau that lasted until the early 1990s, as shown in Chart II-9. There were rapid increases until the global recession. Cyclic factors and not alleged secular stagnation explain the interruption of increases in real hourly compensation.
Chart II-9, US, Nonfarm Business, Real Hourly Compensation, 1947-2020, Index 2012=100
Source: US Bureau of Labor Statistics: https://www.bls.gov/lpc/
© Carlos M. Pelaez, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020.
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