Saturday, October 21, 2017

World Inflation Waves, Long-term and Current US Inflation, United States Industrial Production, Squeeze of Economic Activity by Carry Trades Induced by Zero Interest Rates, Collapse of United States Dynamism of Income Growth and Employment Creation, World Cyclical Slow Growth and Global Recession Risk: Part II

CANNOT UPLOAD CHARTS AND IMAGES

World Inflation Waves, Long-term and Current US Inflation, United States Industrial Production, Squeeze of Economic Activity by Carry Trades Induced by Zero Interest Rates, Collapse of United States Dynamism of Income Growth and Employment Creation, World Cyclical Slow Growth and Global Recession Risk

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

I World Inflation Waves

IA Appendix: Transmission of Unconventional Monetary Policy

IB1 Theory

IB2 Policy

IB3 Evidence

IB4 Unwinding Strategy

IC United States Inflation

IC Long-term US Inflation

ID Current US Inflation

IE Theory and Reality of Economic History, Cyclical Slow Growth Not Secular Stagnation

II United States Industrial Production

IIA Squeeze of Economic Activity by Carry Trades Induced by Zero Interest Rates

II IB Collapse of United Dynamism of Income Growth and Employment Creation

III World Financial Turbulence

IIIA Financial Risks

IIIE Appendix Euro Zone Survival Risk

IIIF Appendix on Sovereign Bond Valuation

IV Global Inflation

V World Economic Slowdown

VA United States

VB Japan

VC China

VD Euro Area

VE Germany

VF France

VG Italy

VH United Kingdom

VI Valuation of Risk Financial Assets

VII Economic Indicators

VIII Interest Rates

IX Conclusion

References

Appendixes

Appendix I The Great Inflation

IIIB Appendix on Safe Haven Currencies

IIIC Appendix on Fiscal Compact

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

IIIG Appendix on Deficit Financing of Growth and the Debt Crisis

IIIGA Monetary Policy with Deficit Financing of Economic Growth

IIIGB Adjustment during the Debt Crisis of the 1980s

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 Ï€*. In that case, (1+ Ï€*) < 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 Ï€* = 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, Ï€*, remains at 1 percent. Suppose now that expectations of deflation become generalized such that Ï€* 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 (http://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

Source: Bureau of Labor Statistics

http://www.bls.gov/cpi/

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

Source: Bureau of Labor Statistics

http://www.bls.gov/ppi/

The producer price index of the US from 1947 to 2017 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, 1947-2017

Source: US Bureau of Labor Statistics

http://www.bls.gov/ppi/

Chart I-17 provides 12-month percentage changes of the producer price index from 1948 to 2017. 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 2017.

Chart I-7, US, Producer Price Index, Finished Goods, 12-Month Percentage Change, NSA, 1948-2017

Source: US Bureau of Labor Statistics

http://www.bls.gov/ppi/

Annual percentage changes of the producer price index from 1948 to 2016 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. There is no evidence in this history of 65 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 ∆% 1948-2016

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

Source: US Bureau of Labor Statistics

http://www.bls.gov/ppi/

Chart I-12 provides the consumer price index NSA from 1918 to 2017. 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, 1918-2017

Source: US Bureau of Labor Statistics http://www.bls.gov/cpi/data.htm

Chart I-13 provides 12-month percentage changes of the consumer price index from 1918 to 2017. 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 1918-2017

Source: US Bureau of Labor Statistics http://www.bls.gov/cpi/data.htm

Table I-2 provides annual percentage changes of United States consumer price inflation from 1914 to 2016. 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. 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 ∆% 1914-2016

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

Source: US Bureau of Labor Statistics http://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 (2005, 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 (1985) 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
PP

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 (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 = ∑isiy*i + ∑iyis*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 63.0 in Sep 2017. 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 to 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/2017/09/dollar-devaluation-world-inflation.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, 1979-2017

Year

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Dec

Annual

1979

63.0

63.2

62.9

62.9

64.5

64.9

64.5

63.8

63.8

63.7

1980

63.2

63.2

63.2

63.5

64.6

65.1

64.5

63.6

63.4

63.8

1981

63.2

63.5

63.6

63.9

64.6

65.0

64.6

63.5

63.4

63.9

1982

63.2

63.4

63.3

63.9

64.8

65.3

64.9

64.0

63.8

64.0

1983

63.2

63.3

63.2

63.4

65.1

65.4

65.1

64.3

63.8

64.0

1984

63.4

63.6

63.7

64.3

65.5

65.9

65.2

64.4

64.3

64.4

1985

64.0

64.4

64.3

64.6

65.5

65.9

65.4

64.9

64.6

64.8

1986

64.4

64.6

64.6

65.0

66.3

66.6

66.1

65.3

65.0

65.3

1987

64.8

65.0

64.9

65.6

66.3

66.8

66.5

65.5

65.5

65.6

1988

65.2

65.2

65.3

65.5

66.7

67.1

66.8

65.9

65.9

65.9

1989

65.6

65.7

65.9

66.2

67.4

67.7

67.2

66.3

66.3

66.5

1990

66.0

66.2

66.1

66.5

67.4

67.7

67.1

66.4

66.1

66.5

1991

65.7

65.9

66.0

66.0

67.2

67.3

66.6

66.1

65.8

66.2

1992

65.8

66.0

66.0

66.4

67.6

67.9

67.2

66.3

66.1

66.4

1993

65.8

65.8

65.6

66.3

67.3

67.5

67.0

66.1

66.2

66.3

1994

66.2

66.1

66.0

66.5

67.2

67.5

67.2

66.5

66.5

66.6

1995

66.2

66.4

66.4

66.4

67.2

67.7

67.1

66.5

66.2

66.6

1996

66.1

66.4

66.2

66.7

67.4

67.9

67.2

66.8

66.7

66.8

1997

66.5

66.9

66.7

67.0

67.8

68.1

67.6

67.0

67.0

67.1

1998

66.7

67.0

66.6

67.0

67.7

67.9

67.3

67.0

67.0

67.1

1999

66.8

66.9

66.7

67.0

67.7

67.9

67.3

66.8

67.0

67.1

2000

67.0

67.1

67.0

67.0

67.7

67.6

67.2

66.7

67.0

67.1

2001

66.8

67.0

66.7

66.6

67.2

67.4

66.8

66.6

66.6

66.8

2002

66.6

66.6

66.4

66.5

67.1

67.2

66.8

66.6

66.2

66.6

2003

66.2

66.2

66.2

66.2

67.0

66.8

66.3

65.9

65.8

66.2

2004

65.7

65.8

65.7

65.8

66.5

66.8

66.2

65.7

65.8

66.0

2005

65.6

65.6

65.8

66.0

66.5

66.8

66.5

66.1

65.9

66.0

2006

65.7

65.8

65.8

66.0

66.7

66.9

66.5

66.1

66.3

66.2

2007

65.8

65.9

65.7

65.8

66.6

66.8

66.1

66.0

65.9

66.0

2008

65.5

65.7

65.7

66.0

66.6

66.8

66.4

65.9

65.7

66.0

2009

65.5

65.4

65.4

65.5

66.2

66.2

65.6

65.0

64.4

65.4

2010

64.6

64.8

64.9

64.8

65.1

65.3

65.0

64.6

64.1

64.7

2011

63.9

64.0

63.9

64.1

64.5

64.6

64.3

64.2

63.8

64.1

2012

63.6

63.6

63.4

63.8

64.3

64.3

63.7

63.6

63.4

63.7

2013

63.2

63.1

63.1

63.5

64.0

64.0

63.4

63.2

62.6

63.2

2014

62.7

62.9

62.6

62.9

63.4

63.5

63.0

62.8

62.5

62.9

2015

62.5

62.5

62.6

63.0

63.1

63.2

62.7

62.3

62.4

62.7

2016

62.7

62.8

62.7

62.7

63.2

63.4

62.9

62.8

62.4

62.8

2017

62.7

62.9

62.8

62.8

63.3

63.5

63.0

63.0

Source: US Bureau of Labor Statistics

http://www.bls.gov/cps/

Chart I-12b, US, Labor Force Participation Rate, Percent of Labor Force in Population, NSA, 1979-2017

Source: Bureau of Labor Statistics

http://www.bls.gov/cps/

Broader perspective is in Chart I-12c of the US Bureau of Labor Statistics. The United States civilian noninstitutional population has increased along a consistent trend since 1948 that continued through earlier recessions and the global recession from IVQ2007 to IIQ2009 and the cyclical expansion after IIIQ2009.

Chart I-12c, US, Civilian Noninstitutional Population, Thousands, NSA, 1948-2017

Sources: US Bureau of Labor Statistics

http://www.bls.gov/data/

The labor force of the United States in Chart I-12d has increased along a trend similar to that of the civilian noninstitutional population in Chart I-12c. There is an evident stagnation of the civilian labor force in the final segment of Chart I-12d during the current economic cycle. This stagnation is explained by cyclical factors similar to those analyzed by Lazear and Spletzer (2012JHJul22) that motivated an increasing population to drop out of the labor force instead of structural factors. Large segments of the potential labor force are not observed, constituting unobserved unemployment and of more permanent nature because those afflicted have been seriously discouraged from working by the lack of opportunities.

Chart I-12d, US, Labor Force, Thousands, NSA, 1948-2017

Sources: US Bureau of Labor Statistics

http://www.bls.gov/data/

The rate of labor force participation in the US is in Chart I-12E from 1948 to 2017. There is sudden decline during the global recession after 2007 without recovery explained by cyclical factors (Lazear and Spletzer2012JHJul22) as may many potential workers stopped their searches disillusioned that there could be an opportunity for them in sharply contracted markets.

Chart I-12E, US, Labor Force Participation Rate, Percent of Labor Force in Population, NSA, 1948-2017

Sources: US Bureau of Labor Statistics

http://www.bls.gov/data/

Chart I-20 provides the level of full-time jobs from 2001 to 2017. 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 255.562 million in Sep 2017 or by 23.604 million (http://www.bls.gov/data/). The number with full-time jobs in Sep 2017 is 127.235 million, which is higher by 4.016 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 135.703 million full-time jobs with population of 255.562 million in Sep 2017 (0.531 x 255.562) or 8.468 million fewer full-time jobs relative to actual 127.235 million. There appear to be around 10 million fewer full-time jobs in the US than before the global recession while population increased around 20 million. Mediocre GDP growth is the main culprit of the fractured US labor market.

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, 2001-2017

Sources: US Bureau of Labor Statistics

http://www.bls.gov/data/

Chart I-20A provides the noninstitutional civilian population of the United States from 2001 to 2017. There is clear trend of increase of the population while the number of full-time jobs collapsed after 2008 without sufficient recovery as shown in the preceding Chart I-20.

Chart I-20A, US, Noninstitutional Civilian Population, Thousands, 2001-2017

Sources: US Bureau of Labor Statistics

http://www.bls.gov/data/

Chart I-20B provides number of full-time jobs in the US from 1968 to 2017. 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, 1968-2017

Sources: US Bureau of Labor Statistics

http://www.bls.gov/data/

Chart I-20C provides the noninstitutional civilian population of the United States from 1968 to 2017. 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, 1968-2017

Sources: US Bureau of Labor Statistics

http://www.bls.gov/data/

Table EMP provides the comparison between the labor market in the current whole cycle from 2007 to 2016 and the whole cycle from 1979 to 1989. In the entire cycle from 2007 to 2016, the number employed increased 5.389 million, full-time employed increased 2.670 million, part-time for economic reasons increased 1.542 million and population increased 21.491 million. The number employed increased 3.7 percent, full-time employed increased 2.2 percent, part-time for economic reasons increased 35.0 percent and population increased 9.3 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

∆2007-2016

5.389

2.670

1.542

21.671

∆% 2007-2016

3.7

2.2

35.0

9.3

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

http://www.bls.gov/

The theory of secular stagnation cannot explain sudden collapse of the US economy and labor markets. There are accentuated cyclic factors for both the entire population and the young population of ages 16 to 24 years. Table Summary Total provides the total noninstitutional population (ICP) of the US, full-time employment level (FTE), employment level (EMP), civilian labor force (CLF), civilian labor force participation rate (CLFP), employment/population ratio (EPOP) and unemployment level (UNE). Secular stagnation would spread over long periods instead of immediately. All indicators of the labor market weakened sharply during the contraction and did not recover. Population continued to grow but all other variables collapsed and did not recover. 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), 11-16). Hansen (1938, 1939) finds secular stagnation in lower growth of an aging population. In the current US economy, Table Summary shows that population is dynamic while the labor market is fractured. There is key explanation in the behavior of the civilian labor force participation rate (CLFP) and the employment population ratio (EPOP) that collapsed during the global recession with inadequate recovery. Abandoning job searches are difficult to capture in labor statistics but likely explain the decline in the participation of the population in the labor force. Allowing for abandoning job searches, the total number of people unemployed or underemployed is 21.1 million or 12.5 percent of the effective labor force (https://cmpassocregulationblog.blogspot.com/2017/10/twenty-one-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2017/09/twenty-two-million-unemployed-or.html).

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

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

9/17

255.6

127.2

154.5

161.0

63.0

60.5

6.6

ICP: Total Noninstitutional Civilian Population; FT: 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

http://www.bls.gov/

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).

Table Summary Youth, US, Youth, Ages 16 to 24 Years, Noninstitutional Civilian Population, Full-time Employment, Employment, Civilian Labor Force, Civilian Labor Force Participation Rate, Employment Population Ratio, Unemployment, NSA, Millions and Percent

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

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

7/17

38.2

20.9

23.1

60.6

54.8

2.2

9.6

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

http://www.bls.gov/

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.”

I United States Industrial Production. There is socio-economic stress in the combination of adverse events and cyclical performance:

and earlier http://cmpassocregulationblog.blogspot.com/2015/07/fluctuating-risk-financial-assets.html and earlier http://cmpassocregulationblog.blogspot.com/2015/06/fluctuating-financial-asset-valuations.html and earlier http://cmpassocregulationblog.blogspot.com/2015/05/fluctuating-valuations-of-financial.html and earlier http://cmpassocregulationblog.blogspot.com/2015/04/global-portfolio-reallocations-squeeze.html and earlier http://cmpassocregulationblog.blogspot.com/2015/03/impatience-with-monetary-policy-of.html and earlier (http://cmpassocregulationblog.blogspot.com/2015/02/world-financial-turbulence-squeeze-of.html and earlier http://cmpassocregulationblog.blogspot.com/2015/01/exchange-rate-conflicts-squeeze-of.html and earlier http://cmpassocregulationblog.blogspot.com/2014/12/patience-on-interest-rate-increases.html and earlier http://cmpassocregulationblog.blogspot.com/2014/11/squeeze-of-economic-activity-by-carry.html and earlier http://cmpassocregulationblog.blogspot.com/2014/10/imf-view-squeeze-of-economic-activity.html and earlier http://cmpassocregulationblog.blogspot.com/2014/09/world-inflation-waves-squeeze-of.html)

Industrial production increased 0.3 percent in Sep 2017 and decreased 0.7 percent in Aug 2017 after decreasing 0.7 percent in Jul 2017, with all data seasonally adjusted, as shown in Table I-1. The Board of Governors of the Federal Reserve System conducted the annual revision of industrial production released on Mar 31, 2017 (https://www.federalreserve.gov/releases/g17/revisions/Current/DefaultRev.htm):

“The Federal Reserve has revised its index of industrial production (IP) and the related measures of capacity and capacity utilization.[1] On net, the revisions were small, and the contour of total IP is little changed. Total IP is still reported to have moved up about 22 percent from the end of the recession in mid-2009 through late 2014, to have declined in 2015, and to have moved sideways in 2016. The most notable difference between the current and the previous estimates is that total IP is now reported to have decreased about 2 3/4 percent in 2015, whereas it previously showed a decline of about 1 3/4 percent.[2] The incorporation of detailed data for manufacturing from the U.S. Census Bureau's 2015 Annual Survey of Manufactures (ASM) accounts for the majority of the differences between the current and the previously published estimates.

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

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

The report of the Board of Governors of the Federal Reserve System states (https://www.federalreserve.gov/releases/g17/Current/default.htm):

“Industrial production rose 0.3 percent in September. The rates of change for July and August were notably revised; the current estimate for July, a decrease of 0.1 percent, was 0.5 percentage point lower than previously reported, while the estimate for August, a decrease of 0.7 percent, was 0.2 percentage point higher than before. The estimates for manufacturing, mining, and utilities were each revised lower in July. The continued effects of Hurricane Harvey and, to a lesser degree, the effects of Hurricane Irma combined to hold down the growth in total production in September by 1/4 percentage point.[1] For the third quarter as a whole, industrial production fell 1.5 percent at an annual rate; excluding the effects of the hurricanes, the index would have risen at least 1/2 percent. Manufacturing output edged up 0.1 percent in September but fell 2.2 percent at an annual rate in the third quarter. The indexes for mining and utilities in September rose 0.4 percent and 1.5 percent, respectively. At 104.6 percent of its 2012 average, total industrial production in September was 1.6 percent above its year-earlier level. Capacity utilization for the industrial sector increased 0.2 percentage point in September to 76.0 percent, a rate that is 3.9 percentage points below its long-run (1972–2016) average.” In the six months ending in Sep 2017, United States national industrial production accumulated change of 0.8 percent at the annual equivalent rate of 1.6 percent, which is equal to growth of 1.6 percent in the 12 months ending in Sep 2017. Excluding growth of 1.1 percent in Apr 2016, growth in the remaining five months from Apr to Sep 2017 accumulated to minus 0.3 percent or minus 0.7 percent annual equivalent. Industrial production decreased 0.7 percent in one of the past six months and decreased 0.1 percent in one month, increasing 0.3 percent in one month, 0.2 percent in one month, 0.0 percent in one month and 1.1 percent in one month. Industrial production decreased at annual equivalent 2.0 percent in the most recent quarter from Jul 2017 to Sep and increased at 5.3 percent in the prior quarter Apr 2017 to Jun 2017. Business equipment accumulated change of 1.0 percent in the six months from Apr 2017 to Sep 2017, at the annual equivalent rate of 2.1 percent, which is equal to growth of 2.1 percent in the 12 months ending in Sep 2017. The Fed analyzes capacity utilization of total industry in its report (https://www.federalreserve.gov/releases/g17/Current/default.htm): “Capacity utilization for the industrial sector increased 0.2 percentage point in September to 76.0 percent, a rate that is 3.9 percentage points below its long-run (1972–2016) average.” United States industry apparently decelerated to a lower growth rate followed by possible acceleration and weakening growth in past months. There could renewed growth.

Table I-1, US, Industrial Production and Capacity Utilization, SA, ∆% 

Sep 17

Aug 17

Jul 

17

Jun 

16

May 

17

Apr 

17

Sep 17/

Sep 16

Total

0.3

-0.7

-0.1

0.2

0.0

1.1

1.6

Market
Groups

Final Products

0.6

-0.5

-0.3

-0.1

0.0

1.8

1.2

Consumer Goods

0.5

-0.6

0.0

-0.2

0.4

1.3

0.2

Business Equipment

0.8

-0.3

-1.2

-0.4

-1.1

3.3

2.1

Non
Industrial Supplies

1.1

-1.2

0.0

-0.2

-0.2

0.4

1.0

Construction

1.9

-1.0

-0.1

-0.2

-0.8

0.5

3.5

Materials

-0.2

-0.8

0.0

0.7

0.0

0.7

2.2

Industry Groups

Manufacturing

0.1

-0.2

-0.4

0.2

-0.6

1.3

1.0

Mining

0.4

-0.2

0.5

1.3

0.8

0.6

9.8

Utilities

1.5

-4.9

0.5

-1.0

2.7

0.2

-4.1

Capacity

76.0

75.8

76.5

76.6

76.5

76.6

1.1

Sources: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/g17/Current/default.htm

Manufacturing increased 0.1 percent in Sep 2017 and decreased 0.2 percent in Aug 2017 after decreasing 0.4 percent in Jul 2017, seasonally adjusted, increasing 1.0 percent not seasonally adjusted in the 12 months ending in Sep 2017, as shown in Table I-2. Manufacturing increased cumulatively 0.4 percent in the six months ending in Sep 2017 or at the annual equivalent rate of 0.8 percent. Excluding the increase of 1.3 percent in Apr 2017, manufacturing decreased 0.9 percent from Apr 2017 to Sep 2017 or at the annual equivalent rate of minus 2.1 percent. Table I-2 provides a longer perspective of manufacturing in the US. There has been evident deceleration of manufacturing growth in the US from 2010 and the first three months of 2011 with recovery followed by renewed deterioration/improvement in more recent months as shown by 12 months’ rates of growth. Growth rates appeared to be increasing again closer to 5 percent in Apr-Jun 2012 but deteriorated. The rates of decline of manufacturing in 2009 are quite high with a drop of 18.5 percent in the 12 months ending in Apr 2009. Manufacturing recovered from this decline and led the recovery from the recession. Rates of growth appeared to be returning to the levels at 3 percent or higher in the annual rates before the recession but the pace of manufacturing fell steadily with some strength at the margin. There is renewed deterioration and improvement. The Board of Governors of the Federal Reserve System conducted the annual revision of industrial production released on Mar 31, 2017 (https://www.federalreserve.gov/releases/g17/revisions/Current/DefaultRev.htm):

“The Federal Reserve has revised its index of industrial production (IP) and the related measures of capacity and capacity utilization.[1] On net, the revisions were small, and the contour of total IP is little changed. Total IP is still reported to have moved up about 22 percent from the end of the recession in mid-2009 through late 2014, to have declined in 2015, and to have moved sideways in 2016. The most notable difference between the current and the previous estimates is that total IP is now reported to have decreased about 2 3/4 percent in 2015, whereas it previously showed a decline of about 1 3/4 percent.[2] The incorporation of detailed data for manufacturing from the U.S. Census Bureau's 2015 Annual Survey of Manufactures (ASM) accounts for the majority of the differences between the current and the previously published estimates.

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

The bottom part of Table I-2 shows decline of manufacturing by 22.3 from the peak in Jun 2007 to the trough in Apr 2009 and increase of 15.5 percent from the trough in Apr 2009 to Dec 2016. Manufacturing grew 19.3 percent from the trough in Apr 2009 to Sep 2017. Manufacturing in Sep 2017 is lower by 7.4 percent relative to the peak in Jun 2007. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. US economic growth has been at only 2.2 percent on average in the cyclical expansion in the 32 quarters from IIIQ2009 to IIQ2017. Boskin (2010Sep) measures that the US economy grew at 6.2 percent in the first four quarters and 4.5 percent in the first 12 quarters after the trough in the second quarter of 1975; and at 7.7 percent in the first four quarters and 5.8 percent in the first 12 quarters after the trough in the first quarter of 1983 (Professor Michael J. Boskin, Summer of Discontent, Wall Street Journal, Sep 2, 2010 http://professional.wsj.com/article/SB10001424052748703882304575465462926649950.html). There are new calculations using the revision of US GDP and personal income data since 1929 by the Bureau of Economic Analysis (BEA) (http://bea.gov/iTable/index_nipa.cfm) and the third estimate of GDP for IIQ2017 (https://www.bea.gov/newsreleases/national/gdp/2017/pdf/gdp2q17_3rd.pdf). The average of 7.7 percent in the first four quarters of major cyclical expansions is in contrast with the rate of growth in the first four quarters of the expansion from IIIQ2009 to IIQ2010 of only 2.7 percent obtained by dividing GDP of $14,745.9 billion in IIQ2010 by GDP of $14,355.6 billion in IIQ2009 {[($14,745.9/$14,355.6) -1]100 = 2.7%], or accumulating the quarter on quarter growth rates (https://cmpassocregulationblog.blogspot.com/2017/10/destruction-of-household-nonfinancial.html and earlier https://cmpassocregulationblog.blogspot.com/2017/09/mediocre-cyclical-united-states.html). The expansion from IQ1983 to IVQ1985 was at the average annual growth rate of 5.9 percent, 5.4 percent from IQ1983 to IIIQ1986, 5.2 percent from IQ1983 to IVQ1986, 5.0 percent from IQ1983 to IQ1987, 5.0 percent from IQ1983 to IIQ1987, 4.9 percent from IQ1983 to IIIQ1987, 5.0 percent from IQ1983 to IVQ1987, 4.9 percent from IQ1983 to IIQ1988, 4.8 percent from IQ1983 to IIIQ1988, 4.8 percent from IQ1983 to IVQ1988, 4.8 percent from IQ1983 to IQ1989, 4.7 percent from IQ1983 to IIQ1989, 4.7 percent from IQ1983 to IIIQ1989, 4.5 percent from IQ1983 to IVQ1989. 4.5 percent from IQ1983 to IQ1990, 4.4 percent from IQ1983 to IIQ1990, 4.3 percent from IQ1983 to IIIQ1990, 4.0 percent from IQ1983 to IVQ1990 and at 7.8 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2017/10/destruction-of-household-nonfinancial.html and earlier https://cmpassocregulationblog.blogspot.com/2017/09/mediocre-cyclical-united-states.html). The National Bureau of Economic Research (NBER) dates a contraction of the US from IQ1990 (Jul) to IQ1991 (Mar) (http://www.nber.org/cycles.html). The expansion lasted until another contraction beginning in IQ2001 (Mar). US GDP contracted 1.3 percent from the pre-recession peak of $8983.9 billion of chained 2009 dollars in IIIQ1990 to the trough of $8865.6 billion in IQ1991 (http://www.bea.gov/iTable/index_nipa.cfm). The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IIQ2017 would have accumulated to 32.4 percent. GDP in IIQ2017 would be $19,849.1 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2818.0 billion than actual $17,031.1 billion. There are about two trillion dollars of GDP less than at trend, explaining the 21.1 million unemployed or underemployed equivalent to actual unemployment/underemployment of 12.5 percent of the effective labor force (https://cmpassocregulationblog.blogspot.com/2017/10/twenty-one-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2017/09/twenty-two-million-unemployed-or.html). US GDP in IIQ2017 is 14.2 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $17,031.1 billion in IIQ2017 or 13.6 percent at the average annual equivalent rate of 1.4 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 3.1 percent per year from Sep 1919 to Sep 2017. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2393 in Dec 2007 to 145.7662 in Sep 2017. The actual index NSA in Sep 2017 is 104.2863, which is 28.5 percent below trend. Manufacturing output grew at average 2.0 percent between Dec 1986 and Sep 2017. Using trend growth of 2.0 percent per year, the index would increase to 131.2915 in Sep 2017. The output of manufacturing at 104.2863 in Sep 2017 is 20.6 percent below trend under this alternative calculation.

Table I-2, US, Monthly and 12-Month Rates of Growth of Manufacturing ∆%

Month SA ∆%

12-Month NSA ∆%

Sep 2017

0.1

1.0

Aug

-0.2

1.2

Jul

-0.4

1.3

Jun

0.2

1.4

May

-0.6

1.5

Apr

1.3

0.1

Mar

-0.7

1.0

Feb

0.3

0.9

Jan

0.4

0.4

Dec 2016

0.2

0.6

Nov

0.2

0.1

Oct

0.2

0.0

Sep

0.2

0.3

Aug

-0.4

-0.8

Jul

0.1

-0.5

Jun

0.2

0.2

May

-0.2

-0.3

Apr

0.0

0.5

Mar

-0.2

-0.7

Feb

-0.2

0.4

Jan

0.6

0.2

Dec 2015

-0.3

-0.9

Nov

-0.1

-0.7

Oct

0.2

0.2

Sep

-0.3

-0.8

Aug

-0.1

0.1

Jul

0.6

0.3

Jun

-0.3

-0.6

May

-0.1

0.2

Apr

0.1

0.3

Mar

0.3

0.3

Feb

-0.5

0.7

Jan

-0.4

2.1

Dec 2014

-0.4

1.7

Nov

0.9

1.9

Oct

0.0

1.1

Sep

0.0

1.2

Aug

-0.4

1.4

Jul

0.2

2.0

Jun

0.3

1.5

May

0.2

1.3

Apr

0.0

0.9

Mar

0.8

1.5

Feb

1.1

0.2

Jan

-1.0

-0.7

Dec 2013

0.0

0.0

Nov

0.0

1.0

Oct

0.1

1.7

Sep

0.1

1.1

Aug

1.0

1.3

Jul

-1.1

0.2

Jun

0.2

0.7

May

0.2

0.9

Apr

-0.4

1.1

Mar

-0.2

0.7

Feb

0.5

0.9

Jan

-0.3

1.0

Dec 2012

0.7

2.0

Nov

0.8

2.0

Oct

-0.2

0.9

Sep

0.0

1.7

Aug

-0.2

2.2

Jul

-0.1

2.5

Jun

0.2

3.3

May

-0.4

3.2

Apr

0.6

3.6

Mar

-0.5

2.5

Feb

0.4

3.8

Jan

0.9

3.2

Dec 2011

0.6

2.8

Nov

-0.4

2.3

Oct

0.6

2.5

Sep

0.3

2.3

Aug

0.4

1.9

Jul

0.5

2.2

Jun

0.1

1.8

May

0.1

1.6

Apr

-0.6

2.9

Mar

0.6

4.5

Feb

0.1

5.1

Jan

0.2

5.2

Dec 2010

0.4

5.8

Nov

0.0

4.9

Oct

0.1

6.1

Sep

0.1

6.4

Aug

0.2

7.0

Jul

0.6

7.5

Jun

-0.1

9.2

May

1.4

8.7

Apr

0.9

6.9

Mar

1.2

4.6

Feb

-0.1

1.2

Jan

1.1

1.1

Dec 2009

-0.2

-3.4

Nov

1.0

-6.3

Oct

0.2

-9.3

Sep

0.8

-10.7

Aug

1.2

-13.7

Jul

1.4

-15.4

Jun

-0.4

-18.0

May

-1.1

-17.8

Apr

-0.8

-18.5

Mar

-1.9

-17.4

Feb

-0.2

-16.3

Jan

-3.0

-16.6

Dec 2008

-3.5

-14.1

Nov

-2.3

-11.4

Oct

-0.6

-8.9

Sep

-3.4

-8.7

Aug

-1.1

-5.2

Jul

-1.2

-3.7

Jun

-0.6

-3.3

May

-0.5

-2.6

Apr

-1.1

-1.3

Mar

-0.3

-0.8

Feb

-0.6

0.8

Jan

-0.4

2.1

Dec 2007

0.1

1.8

Nov

0.5

3.3

Oct

-0.4

2.7

Sep

0.4

2.9

Aug

-0.3

2.7

Jul

0.1

3.6

Jun

0.3

3.1

May

-0.1

3.2

Apr

0.7

3.7

Mar

0.8

2.6

Feb

0.4

1.6

Jan

-0.5

1.3

Dec 2006

2.7

Dec 2005

3.5

Dec 2004

4.0

Dec 2003

2.2

Dec 2002

2.4

Dec 2001

-5.4

Dec 2000

0.8

Dec 1999

5.2

Average ∆% Dec 1986-Dec 2016

2.0

Average ∆% Dec 1986-Dec 2015

2.0

Average ∆% Dec 1986-Dec 2014

2.1

Average ∆% Dec 1986-Dec 2013

2.2

Average ∆% Dec 1986-Dec 1999

4.3

Average ∆% Dec 1999-Dec 2006

1.4

Average ∆% Dec 1999-Dec 2016

0.3

∆% Peak 112.5742 in 06/2007 to 100.9324 in 12/2016

-10.3

∆% Peak 112.5742 in 06/2007 to Trough 87.4229 in 4/2009

-22.3

∆% Trough 87.4229 in 04/2009 to 100.9324 in 12/2016

15.5

∆% Trough 87.4229 in 04/2009 to 104.2863 in 9/2017

19.3

∆% Peak 112.5742 on 06/2007 to 104.2863 in 9/2017

-7.4

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/g17/Current/default.htm

Chart I-1 of the Board of Governors of the Federal Reserve System provides industrial production, manufacturing and capacity since the 1970s. There was acceleration of growth of industrial production, manufacturing and capacity in the 1990s because of rapid growth of productivity in the US (Cobet and Wilson (2002); see Pelaez and Pelaez, The Global Recession Risk (2007), 135-44). The slopes of the curves flatten in the 2000s. Production and capacity have not recovered sufficiently above levels before the global recession, remaining like GDP below historical trend. 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 3.1 percent per year from Jul 1919 to Jul 2017. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2393 in Dec 2007 to 145.0407 in Jul 2017. The actual index NSA in Jul 2017 is 102.1551, which is 29.6 percent below trend. Manufacturing output grew at average 2.0 percent between Dec 1986 and Jul 2017. Using trend growth of 2.0 percent per year, the index would increase to 130.8588 in Jul 2017. The output of manufacturing at 102.1551 in Jul 2017 is 21.9 percent below trend under this alternative calculation.

Chart I-1, US, Industrial Production, Capacity and Utilization

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/g17/Current/ipg1.gif

The modern industrial revolution of Jensen (1993) is captured in Chart I-2 of the Board of Governors of the Federal Reserve System (for the literature on M&A and corporate control see Pelaez and Pelaez, Regulation of Banks and Finance (2009a), 143-56, Globalization and the State, Vol. I (2008a), 49-59, Government Intervention in Globalization (2008c), 46-49). The slope of the curve of total industrial production accelerates in the 1990s to a much higher rate of growth than the curve excluding high-technology industries. Growth rates decelerate into the 2000s and output and capacity utilization have not recovered fully from the strong impact of the global recession. Growth in the current cyclical expansion has been more subdued than in the prior comparably deep contractions in the 1970s and 1980s. Chart I-2 shows that the past recessions after World War II are the relevant ones for comparison with the recession after 2007 instead of common comparisons with the Great Depression (https://cmpassocregulationblog.blogspot.com/2017/10/destruction-of-household-nonfinancial.html and earlier https://cmpassocregulationblog.blogspot.com/2017/09/mediocre-cyclical-united-states.html)). The bottom left-hand part of Chart II-2 shows the strong growth of output of communication equipment, computers and semiconductor that continued from the 1990s into the 2000s. Output of semiconductors has already surpassed the level before the global recession.

Chart I-2, US, Industrial Production, Capacity and Utilization of High Technology Industries

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/g17/Current/ipg3.gif

Additional detail on industrial production and capacity utilization is in Chart I-3 of the Board of Governors of the Federal Reserve System. Production of consumer durable goods fell sharply during the global recession by more than 30 percent and is oscillating above the level before the contraction. Output of nondurable consumer goods fell around 10 percent and is some 5 percent below the level before the contraction. Output of business equipment fell sharply during the contraction of 2001 but began rapid growth again after 2004. An important characteristic is rapid growth of output of business equipment in the cyclical expansion after sharp contraction in the global recession, stalling in the final segment. Output of defense and space only suffered reduction in the rate of growth during the global recession and surged ahead of the level before the contraction, declining in the final segment. Output of construction supplies collapsed during the global recession and is well below the level before the contraction. Output of energy materials was stagnant before the contraction but recovered sharply above the level before the contraction with recent decline.

Chart I-3, US, Industrial Production and Capacity Utilization

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/g17/Current/ipg2.gif

United States manufacturing output from 1919 to 2017 on a monthly basis is in Chart I-4 of the Board of Governors of the Federal Reserve System. The second industrial revolution of Jensen (1993) is quite evident in the acceleration of the rate of growth of output given by the sharper slope in the 1980s and 1990s. Growth was robust after the shallow recession of 2001 but dropped sharply during the global recession after IVQ2007. Manufacturing output recovered sharply but has not reached earlier levels and is losing momentum at the margin. Current output is well below extrapolation of trend. 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 3.1 percent per year from Sep 1919 to Sep 2017. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2393 in Dec 2007 to 145.7662 in Sep 2017. The actual index NSA in Sep 2017 is 104.2863, which is 28.5 percent below trend. Manufacturing output grew at average 2.0 percent between Dec 1986 and Sep 2017. Using trend growth of 2.0 percent per year, the index would increase to 131.2915 in Sep 2017. The output of manufacturing at 104.2863 in Sep 2017 is 20.6 percent below trend under this alternative calculation.

Chart I-4, US, Manufacturing Output, 1919-2017

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/g17/Current/default.htm

Manufacturing jobs not seasonally adjusted increased 142,000 from Aug 2016 to
Aug 2017 or at the average monthly rate of 11,833.   Industrial production decreased 0.9 percent in Aug 2017 and increased 0.4 percent in Jul 2017 after increasing 0.2 percent in Jun 2017, with all data seasonally adjusted. The Board of Governors of the Federal Reserve System conducted the annual revision of industrial production released on Mar 31, 2017 (https://www.federalreserve.gov/releases/g17/revisions/Current/DefaultRev.htm

Manufacturing jobs not seasonally adjusted increased 118,000 from Sep 2016 to
Sep 2017 or at the average monthly rate of 9,833. Industrial production increased 0.3 percent in Sep 2017 and decreased 0.7 percent in Aug 2017 after decreasing 0.7 percent in Jul 2017, with all data seasonally adjusted. The Board of Governors of the Federal Reserve System conducted the annual revision of industrial production released on Mar 31, 2017 (https://www.federalreserve.gov/releases/g17/revisions/Current/DefaultRev.htm):

“The Federal Reserve has revised its index of industrial production (IP) and the related measures of capacity and capacity utilization.[1] On net, the revisions were small, and the contour of total IP is little changed. Total IP is still reported to have moved up about 22 percent from the end of the recession in mid-2009 through late 2014, to have declined in 2015, and to have moved sideways in 2016. The most notable difference between the current and the previous estimates is that total IP is now reported to have decreased about 2 3/4 percent in 2015, whereas it previously showed a decline of about 1 3/4 percent.[2] The incorporation of detailed data for manufacturing from the U.S. Census Bureau's 2015 Annual Survey of Manufactures (ASM) accounts for the majority of the differences between the current and the previously published estimates.

Capacity for total industry is now reported to have expanded about 1 percent in 2015, a lower rate of increase than was reported earlier. Capacity was little changed in 2016 and is expected to increase 1 percent in 2017. Compared with prior reports, the rates of change in 2016 and 2017 are now a little smaller. In the fourth quarter of 2016, capacity utilization for total industry stood at 75.8 percent, a rate 0.4 percentage point higher than previously published but still 4.1 percentage points below its long-run (1972–2016) average. Relative to earlier estimates, the utilization rates in recent years are now a little higher.” Manufacturing fell 22.3 from the peak in Jun 2007 to the trough in Apr 2009 and increased 15.5 percent from the trough in Apr 2009 to Dec 2016. Manufacturing grew 19.3 percent from the trough in Apr 2009 to Sep 2017. Manufacturing in Sep 2017 is lower by 7.4 percent relative to the peak in Jun 2007. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Growth at trend in the entire cycle from IVQ2007 to IIQ2017 would have accumulated to 32.4 percent. GDP in IIQ2017 would be $19,849.1 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2818.0 billion than actual $17,031.1 billion. There are about two trillion dollars of GDP less than at trend, explaining the 21.1 million unemployed or underemployed equivalent to actual unemployment/underemployment of 12.5 percent of the effective labor force (https://cmpassocregulationblog.blogspot.com/2017/10/twenty-one-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2017/09/twenty-two-million-unemployed-or.html). US GDP in IIQ2017 is 14.2 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $17,031.1 billion in IIQ2017 or 13.6 percent at the average annual equivalent rate of 1.4 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 3.1 percent per year from Sep 1919 to Sep 2017. Growth at 3.1 percent per year would raise the NSA index of manufacturing output from 108.2393 in Dec 2007 to 145.7662 in Sep 2017. The actual index NSA in Sep 2017 is 104.2863, which is 28.5 percent below trend. Manufacturing output grew at average 2.0 percent between Dec 1986 and Sep 2017. Using trend growth of 2.0 percent per year, the index would increase to 131.2915 in Sep 2017. The output of manufacturing at 104.2863 in Sep 2017 is 20.6 percent below trend under this alternative calculation.

Table I-13 provides national income by industry without capital consumption adjustment (WCCA). “Private industries” or economic activities have share of 87.1 percent in IIQ2017. Most of US national income is in the form of services. In Sep 2017, there were 146.880 million nonfarm jobs NSA in the US, according to estimates of the establishment survey of the Bureau of Labor Statistics (BLS) (http://www.bls.gov/news.release/empsit.nr0.htm Table B-1). Total private jobs of 124.604 million NSA in Aug 2017 accounted for 84.8 percent of total nonfarm jobs of 146.880 million, of which 12.490 million, or 10.0 percent of total private jobs and 8.5 percent of total nonfarm jobs, were in manufacturing. Private service-providing jobs were 104.269 million NSA in Sep 2017, or 71.0 percent of total nonfarm jobs and 83.7 percent of total private-sector jobs. Manufacturing has share of 10.1 percent in US national income in IIQ2017 and durable goods 5.9 percent, as shown in Table I-13. Most income in the US originates in services. Subsidies and similar measures designed to increase manufacturing jobs will not increase economic growth and employment and may actually reduce growth by diverting resources away from currently employment-creating activities because of the drain of taxation.

Table I-13, US, National Income without Capital Consumption Adjustment by Industry, Seasonally Adjusted Annual Rates, Billions of Dollars, % of Total

SAAR IQ2017

% Total

SAAR IIQ2017

% Total

National Income WCCA

16,281.6

100.0

16,426.5

100.0

Domestic Industries

16,067.4

98.7

16,224.1

98.8

Private Industries

14,157.8

87.0

14,303.4

87.1

Agriculture

134.1

0.8

114.9

0.7

Mining

142.0

0.9

156.8

1.0

Utilities

195.2

1.2

196.6

1.2

Construction

815.9

5.0

817.2

5.0

Manufacturing

1630.1

10.0

1657.2

10.1

Durable Goods

960.2

5.9

973.2

5.9

Nondurable Goods

670.0

4.1

684.0

4.2

Wholesale Trade

908.5

5.6

934.4

5.7

Retail Trade

1132.0

7.0

1147.3

7.0

Transportation & WH

503.8

3.1

527.0

3.2

Information

612.0

3.8

623.4

3.8

Finance, Insurance, RE

2906.0

17.8

2878.8

17.5

Professional & Business Services

2333.0

14.3

2369.4

14.4

Education, Health Care

1652.0

10.1

1673.2

10.2

Arts, Entertainment

714.8

4.4

724.3

4.4

Other Services

478.1

2.9

482.9

2.9

Government

1909.6

11.7

1920.7

11.7

Rest of the World

214.3

1.3

202.4

1.2

Notes: SSAR: Seasonally-Adjusted Annual Rate; WCCA: Without Capital Consumption Adjustment by Industry; WH: Warehousing; RE, includes rental and leasing: Real Estate; Art, Entertainment includes recreation, accommodation and food services; BS: business services

Source: US Bureau of Economic Analysis

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

Motor vehicle sales and production in the US have been in long-term structural change. Table VA-1A provides the data on new motor vehicle sales and domestic car production in the US from 1990 to 2010. New motor vehicle sales grew from 14,137 thousand in 1990 to the peak of 17,806 thousand in 2000 or 29.5 percent. In that same period, domestic car production fell from 6,231 thousand in 1990 to 5,542 thousand in 2000 or -11.1 percent. New motor vehicle sales fell from 17,445 thousand in 2005 to 11,772 in 2010 or 32.5 percent while domestic car production fell from 4,321 thousand in 2005 to 2,840 thousand in 2010 or 34.3 percent. In Sep 2017, light vehicle sales accumulated to 12,874,473 million, which is lower by 1.8 percent relative to 13,107,087 a year earlier (http://www.motorintelligence.com/m_frameset.html). The seasonally adjusted annual rate of light vehicle sales in the US reached 18.57 million in Sep 2017, higher than 16.14 million in Aug 2017 and higher than 17.72 million in Sep 2016. (http://www.motorintelligence.com/m_frameset.html).

Table VA-1A, US, New Motor Vehicle Sales and Car Production, Thousand Units 7

New Motor Vehicle Sales

New Car Sales and Leases

New Truck Sales and Leases

Domestic Car Production

1990

14,137

9,300

4,837

6,231

1991

12,725

8,589

4,136

5,454

1992

13,093

8,215

4,878

5,979

1993

14,172

8,518

5,654

5,979

1994

15,397

8,990

6,407

6,614

1995

15,106

8,536

6,470

6,340

1996

15,449

8,527

6,922

6,081

1997

15,490

8,273

7,218

5,934

1998

15,958

8,142

7,816

5,554

1999

17,401

8,697

8,704

5,638

2000

17,806

8,852

8,954

5,542

2001

17,468

8,422

9,046

4,878

2002

17,144

8,109

9,036

5,019

2003

16,968

7,611

9,357

4,510

2004

17,298

7,545

9,753

4,230

2005

17,445

7,720

9,725

4,321

2006

17,049

7,821

9,228

4,367

2007

16,460

7,618

8,683

3,924

2008

13,494

6,814

6.680

3,777

2009

10,601

5,456

5,154

2,247

2010

11,772

5,729

6,044

2,840

Source: US Census Bureau

http://www.census.gov/compendia/statab/cats/wholesale_retail_trade/motor_vehicle_sales.html

Chart I-5 of the Board of Governors of the Federal Reserve provides output of motor vehicles and parts in the United States from 1972 to 2017. Output virtually stagnated since the late 1990s with recent increase.

Chart I-5 of the Board of Governors of the Federal Reserve provides output of motor vehicles and parts in the United States from 1972 to 2017. Output virtually stagnated since the late 1990s with recent increase.

Chart 1-5, US, Motor Vehicles and Parts Output, 1972-2017

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/g17/Current/default.htm

Chart I-6 of the Board of Governors of the Federal Reserve System provides output of computers and electronic products in the United States from 1972 to 2017. Output accelerated sharply in the 1990s and 2000s and surpassed the level before the global recession beginning in IVQ2007.

Chart I-6, US, Output of Computers and Electronic Products, 1972-2017

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/g17/Current/default.htm

Chart I-7 of the Board of Governors of the Federal Reserve System shows that output of durable manufacturing accelerated in the 1980s and 1990s with slower growth in the 2000s perhaps because processes matured. Growth was robust after the major drop during the global recession but appears to vacillate in the final segment.

Chart I-7, US, Output of Durable Manufacturing, 1972-2017

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/g17/Current/default.htm

Chart I-8 of the Board of Governors of the Federal Reserve System provides output of aerospace and miscellaneous transportation equipment from 1972 to 2017. There is long-term upward trend with oscillations around the trend and cycles of large amplitude.

Chart I-8, US, Output of Aerospace and Miscellaneous Transportation Equipment, 1972-2017

Source: Board of Governors of the Federal Reserve System

https://www.federalreserve.gov/releases/g17/Current/default.htm

The Empire State Manufacturing Survey Index in Table VA-1 provides continuing deterioration that started in Jun 2012 well before Hurricane Sandy in Oct 2012. The current general index has been in negative contraction territory from minus 2.2 in Aug 2012 to minus 7.6 in Jan 2013 and minus 2.1 in May 2013. The current general index changed to 30.2 in Oct 2017. The index of current orders has also been in negative contraction territory from minus 2.9 in Aug 2012 to minus 9.8 in Jan 2013 and minus 7.9 in Jun 2013. The index of current new orders changed to 18.0 in Oct 2017. There is improvement in the general index for the next six months at 44.8 in Oct 2017 and new orders at 44.8.

Table VA-1, US, New York Federal Reserve Bank Empire State Manufacturing Survey Index SA

Current General Index

Current New Orders

Future General Index

Future New Orders

9/30/2011

-4

-3.6

22.1

23.5

10/31/2011

-5.1

2.8

14.3

19.7

11/30/2011

4.9

1.2

35.5

31.2

12/31/2011

11.5

9.4

46.2

43.6

1/31/2012

11.4

9.2

51.3

44.6

2/29/2012

17.4

7

46.7

38.7

3/31/2012

15.4

4.2

43.9

37.8

4/30/2012

7.6

4.5

40.2

37.4

5/31/2012

13.6

7.7

31.9

31.1

6/30/2012

1.5

1.5

27.5

28.4

7/31/2012

2.5

-4

23.7

20.9

8/31/2012

-2.2

-2.9

19.3

14.1

9/30/2012

-6.4

-9.4

26.3

28

10/31/2012

-3.5

-5.5

20

22.6

11/30/2012

-0.8

5.6

18.4

16.9

12/31/2012

-6

-1

19.8

19.3

1/31/2013

-7.6

-9.8

22

23.8

2/28/2013

8.9

12.6

32.9

28.6

3/31/2013

5.3

4.9

35

33

4/30/2013

4.2

1.6

30

34.3

5/31/2013

-2.1

-2.4

25.7

29.2

6/30/2013

4.8

-7.9

27.6

22.5

7/31/2013

4.3

2.1

33

32.1

8/31/2013

10.7

2.5

36.5

30.3

9/30/2013

8.3

4.1

39.5

38.2

10/31/2013

5.3

10.1

41.2

37.1

11/30/2013

2.2

-2.8

38.5

41.4

12/31/2013

2.5

-0.8

37.6

27.9

1/31/2014

12.3

9

36.4

37.6

2/28/2014

6.1

2.4

41.1

45.6

3/31/2014

3.6

2.1

35.1

36.4

4/30/2014

3.5

-2.5

37.8

32.9

5/31/2014

16.3

8.5

42.6

37.1

6/30/2014

16.4

13.6

41.2

44.5

7/31/2014

19.5

16.7

29.4

26.1

8/31/2014

17.6

15.2

46.5

50

9/30/2014

30.2

19.2

45.6

45.9

10/31/2014

8.4

2

42

42.4

11/30/2014

12

10

48.1

49.6

12/31/2014

-3.4

-1

36.9

35.9

1/31/2015

11.8

6.6

47.3

40.9

2/28/2015

9.6

3.5

29

31.8

3/31/2015

4.5

-3.9

30.8

26.1

4/30/2015

-0.8

-7.5

36.1

31.9

5/31/2015

2.3

2.1

29.8

33.3

6/30/2015

-4.1

-5.4

26

27.2

7/31/2015

0.1

-4.9

27.9

31.8

8/31/2015

-12

-14.7

34

30.4

9/30/2015

-12.2

-10.2

22.1

24

10/31/2015

-10.4

-15

22.3

23

11/30/2015

-9.6

-11.2

23.6

23.7

12/31/2015

-7.3

-6.7

35.2

24.8

1/31/2016

-16.8

-22.4

10.4

14

2/29/2016

-14.5

-9.7

17.1

24.1

3/31/2016

-1.5

6.4

25.3

36.8

4/30/2016

8.4

7.9

28.9

34.8

5/31/2016

-9

-4.7

27.7

21.9

6/30/2016

3.7

8.2

33.3

37.6

7/31/2016

-0.5

-1.7

29.5

29.5

8/31/2016

-3.2

1

26.9

28.4

9/30/2016

-1.2

-5

33

32.5

10/31/2016

-5.5

-3.1

35.3

38

11/30/2016

2.2

4

31.1

31.3

12/31/2016

7.6

10.4

49.7

46.3

1/31/2017

6.5

3.1

49.7

39.8

2/28/2017

18.7

13.5

41.7

43.8

3/31/2017

16.4

21.3

37.4

33.9

4/30/2017

5.2

7

39.9

31

5/31/2017

-1

-4.4

39.3

33.2

6/30/2017

19.8

18.1

41.7

42.2

7/31/2017

9.8

13.3

34.9

33.4

8/31/2017

25.2

20.6

45.2

41.3

9/30/2017

24.4

24.9

39.3

43.7

10/31/2017

30.2

18

44.8

44.8

Source: Federal Reserve Bank of New York

http://www.ny.frb.org/survey/empire/empiresurvey_overview.html

Chart VA-1 of the Federal Reserve Bank of New York provides indexes of current and expected economic activity. There were multiple contractions in current activity after the global recession shown in shade. Current activity is weakening relative to strong recovery in the initial expansion in 2010 and 2011 with recent recovery.

Chart VA-1, US, US, Federal Reserve Bank of New York, Diffusion Index of Current and Expected Activity, Seasonally Adjusted

Source: Federal Reserve Bank of New York

http://www.ny.frb.org/survey/empire/empiresurvey_overview.html

Table VA-2 shows improvement after prior deterioration followed by current soft improvement of the Business Outlook survey of the Federal Reserve Bank of Philadelphia. The general index moved out of contraction of 4.8 in Feb 2013 to expansion at 27.9 in Oct 2017. New orders moved from 0.1 in Feb 2013 to 19.6 in Oct 2017. There is improvement in the future general index at 43.7 in Oct 2017 and in future new orders at 45.3 in Oct 2017.

Table VA-2, US, Federal Reserve Bank of Philadelphia Business Outlook Survey, SA

Current General Index

Current New Orders

Future General Index

Future New Orders

Jan-11

16.5

20.7

36.2

38.1

Feb-11

29

21

38.8

43.9

Mar-11

36.5

34.7

55.6

54.8

Apr-11

12.9

14.4

30.8

36.5

May-11

6.2

8.5

25.1

28.7

Jun-11

-0.3

-4.5

8.4

8.4

Jul-11

7.2

2.8

32.2

27.6

Aug-11

-19.4

-17.9

26.6

23.4

Sep-11

-11.5

-6.5

19.6

21.8

Oct-11

6.2

5.1

28.6

29.6

Nov-11

4

0.3

36.3

33.8

Dec-11

2.4

4.7

38.7

31.7

Jan-12

7.4

11.1

44

43.9

Feb-12

10.7

12.1

32.4

28.4

Mar-12

8.9

1.3

37.3

31.1

Apr-12

5.6

1.6

42

35

May-12

-0.7

2.8

35.4

30.6

Jun-12

-12.4

-16.7

33.6

36.7

Jul-12

-12.6

-5.4

25.5

19.1

Aug-12

-2.3

0.5

25.3

17.6

Sep-12

-0.9

0.3

42.6

34.7

Oct-12

-1.2

-4.9

20.6

20.6

Nov-12

-10.6

-9.1

23.3

24.2

Dec-12

2.4

2.9

29.2

27.4

Jan-13

-1.6

-2

32.4

37.4

Feb-13

-4.8

0.1

39.4

34.1

Mar-13

2.3

2.6

38.5

34.4

Apr-13

0.6

1.8

34.1

34.3

May-13

0.5

-2.9

42.1

38.3

Jun-13

12.9

12.9

38.7

39

Jul-13

15.9

4.9

51.9

43.6

Aug-13

8.4

8

38.3

39.4

Sep-13

19.2

19.4

51.1

47.9

Oct-13

12.9

22.4

60.6

51.3

Nov-13

4.4

7

47.5

41.2

Dec-13

3.2

11.9

44.9

39.5

Jan-14

14.9

7.8

41.9

38.9

Feb-14

3.3

4.2

40.6

43.2

Mar-14

13.4

10.3

39.6

47.3

Apr-14

17.5

18.3

38.6

41.2

May-14

19.3

15.7

42

42.7

Jun-14

14.3

11.6

52.7

46.4

Jul-14

20.7

25.3

47.4

50.2

Aug-14

23

14.8

50.3

58.4

Sep-14

20.4

14.7

44.2

50.8

Oct-14

17.7

15.5

48.2

49.3

Nov-14

34.8

27.2

47

48.2

Dec-14

20.3

13.9

44.9

44.3

Jan-15

12.5

9.9

48.7

47.8

Feb-15

12.5

8.9

48

44.9

Mar-15

8.6

6.5

39.5

38.5

Apr-15

10.4

5.3

34.1

39.5

May-15

8.2

6.2

33.9

32.9

Jun-15

8.1

11.7

43.1

54

Jul-15

2.9

-1.6

42.2

44.3

Aug-15

5.4

5.6

37.9

28

Sep-15

-4.8

11.9

40.9

38.9

Oct-15

-4.9

-8.6

35.5

33.8

Nov-15

-4.3

-10.5

48.3

41.6

Dec-15

-11.3

-9.9

32.1

32

Jan-16

-5.3

-2.7

23.6

26.1

Feb-16

-3.8

-3.9

22.6

22.8

Mar-16

10.6

12.7

37.6

34.2

Apr-16

-1.2

-0.4

44.2

40

May-16

-1.5

-1.5

38.2

35.6

Jun-16

4.1

-1.1

31.3

33.8

Jul-16

-0.9

6.1

30.9

28.6

Aug-16

4.3

-3.4

41.3

45.4

Sep-16

11.6

5.3

37.3

32.8

Oct-16

11.1

17.3

39.6

39.8

Nov-16

8.7

15.2

41.1

31.7

Dec-16

19.7

14.9

48.8

46.7

Jan-17

23.6

26

54.5

59.1

Feb-17

43.3

38

51.5

51.7

Mar-17

32.8

38.6

61

54.8

Apr-17

22

27.4

55.9

44.7

May-17

38.8

25.4

47.2

38.5

Jun-17

27.6

25.9

31.9

38.7

Jul-17

19.5

2.1

39.4

25.9

Aug-17

18.9

20.4

49.1

44.1

Sep-17

23.8

29.5

56.9

55.8

Oct-17

27.9

19.6

43.7

45.3

Source: Federal Reserve Bank of Philadelphia

https://www.philadelphiafed.org/

Chart VA-2 of the Federal Reserve Bank of Philadelphia is very useful, providing current and future general activity indexes from Jan 2006 to May 2016. The shaded areas are the recession cycle dates of the National Bureau of Economic Research (NBER) (http://www.nber.org/cycles.html). The Philadelphia Fed index dropped during the initial period of recession and then led the recovery, as industry overall. There was a second decline of the index into 2011 followed now by what appeared as renewed strength from late 2011 into Jan 2012. There is decline to negative territory of the current activity index in Nov 2012 and return to positive territory in Dec 2012 with decline of current conditions into contraction in Jan-Feb 2013 and rebound to mild expansion in Mar-Apr 2013. The index of current activity moved into expansion in Jun-Oct 2013 with weakness in Nov-Dec 2013, improving in Jan 2014. There is renewed deterioration in Feb 2014 with rebound in Apr-Sep 2014 and mild deterioration in Oct 2014 followed by improvement in Nov 2014. The index deteriorated in Jan-Feb 2015, stabilizing in Mar-May 2015 and improving in Jun 2015. The index deteriorated in Jul 2015, improved in Aug 2015 and deteriorated in Sep-Oct 2015. The index shows contraction in Nov 2015 to Feb 2016 with recovery in Mar 2016. There is deterioration in Apr-May 2016 with improvement in Jun 2016 and deterioration in Jul 2016. There is improvement in Aug-Sep 2016 with moderate weakening in Oct-Nov 2016. The indexes improved sharply in Dec 2016 and Jan-Feb 2017, softening in Mar-Apr 2017. The current index weakened in Jun 2017 with stability in the six-month forecast. The current index deteriorated in Jul 2017 with improvement in the six-month forecast. The current index deteriorated in Aug 2017 with improvement in the six-month forecast. The current index improved in Sep 2017 with improvement in the six-month forecast. The current index and the future index deteriorated in Oct 2017.

Chart VA-2, Federal Reserve Bank of Philadelphia Business Outlook Survey, Current and Future Activity Indexes

Source: Federal Reserve Bank of Philadelphia

https://www.philadelphiafed.org/

The index of current new orders of the Business Outlook Survey of the Federal Reserve Bank of Philadelphia in Chart VA-2 illustrates the weakness of the cyclical expansion. The index weakened in 2006 and 2007 and then fell sharply into contraction during the global recession. There have been twelve readings into contraction from Jan 2012 to May 2013 and generally weak readings with some exceptions. The index of new orders moved into expansion in Jun-Oct 2013 with moderation in Nov-Dec 2013 and into Jan 2014. The index fell into contraction in Feb 2014, recovering in Mar-Apr 2014 but weaker reading in May 2014. There is marked improvement in Jun-Jul 2014 with slowing in Aug-Oct 2014 followed by acceleration in Nov 2014. New orders deteriorated in Jan-Apr 2015, improving in May-Jun 2015. New orders deteriorated in Jul-Aug 2015 and improved in Sep 2015. New orders deteriorated in Oct-2015 to Dec 2015, contracting at slower pace in Jan 2016. There is sharper contraction in Feb 2016 and an upward jump in Mar 2016 followed by deterioration in Apr-Jun 2016. New orders improved in Jul 2016, deteriorating in Aug 2016 and improving in Sep 2016. Improvement continued in Oct-Nov 2016 with mild deterioration in Dec 2016 followed by improvement in Jan-Feb 2017, softening in Mar-Jul 2017, recovering in Aug-Sep 2017. There is deterioration in Oct 2017.

Chart VA-3, Federal Reserve Bank of Philadelphia Business Outlook Survey, Current New Orders Diffusion Index SA

Source: Federal Reserve Bank of Philadelphia

https://www.philadelphiafed.org/

IIA Squeeze of Economic Activity by Carry Trades Induced by Zero Interest Rates. Long-term economic growth in Japan significantly improved by increasing competitiveness in world markets. Net trade of exports and imports is an important component of the GDP accounts of Japan. Table VB-3 provides quarterly data for net trade, exports and imports of Japan. Net trade had strong positive contributions to GDP growth in Japan in all quarters from IQ2007 to IIQ2009 with exception of IVQ2008, IIIQ2008 and IQ2009. The US recession is dated by the National Bureau of Economic Research (NBER) as beginning in IVQ2007 (Dec) and ending in IIQ2009 (Jun) (http://www.nber.org/cycles/cyclesmain.html). Net trade contributions helped to cushion the economy of Japan from the global recession. Net trade deducted from GDP growth in seven of the nine quarters from IVQ2010 to IQ2012. The only strong contribution of net trade was 3.6 percent in IIIQ2011. Net trade added 1.4 percentage points to GDP growth in IQ2013 but subtracted 0.1 percentage points in IIQ2013, deducting 1.3 percentage points in IIIQ2013 and 2.2 percentage points in IVQ2013. Net trade deducted 0.8 percentage points from GDP growth in IQ2014. Net trade added 4.0 percentage points to GDP growth in IIQ2014 and deducted 0.2 percentage points in IIIQ2014. Net trade added 1.5 percentage points to GDP growth in IVQ2014. Net trade contributed 0.0 percentage points to GDP growth in IQ2015 and deducted 0.5-percentage points in IIQ2015. Net trade deducted 0.3 percentage points from GDP growth in IIIQ2015. Net trade contributed 0.0 percentage points to GDP growth in IVQ2015 and added 1.4 percentage points in IQ2016. Net trade contributed 0.2 percentage points to GDP growth in IIQ2016. Net trade added 1.6 percentage points to GDP growth in IIIQ2016 and contributed 1.3 percentage points in IVQ2016.  Net trade contributed 0.5 percentage points to GDP growth in IQ2017 and deducted 1.2 percentage points in IIQ2017. Private consumption assumed the role of driver of Japan’s economic growth but should moderate as in most mature economies.

Table VB-3, Japan, Contributions to Changes in Real GDP, Seasonally Adjusted Annual Rates (SAAR), %

Net Trade

Exports

Imports

2017

I

0.5

1.3

-0.8

II

-1.2

-0.3

-0.9

2016

I

1.4

0.0

1.5

II

0.2

-0.6

0.8

III

1.6

1.5

0.2

IV

1.3

2.2

-0.9

2015

I

0.0

0.8

-0.8

II

-0.5

-2.6

2.1

III

-0.3

1.7

-1.9

IV

0.0

-0.3

0.2

2014

I

-0.8

3.8

-4.6

II

4.0

0.8

3.2

III

-0.2

1.0

-1.2

IV

1.5

2.4

-0.9

2013

I

1.4

1.7

-0.3

II

-0.1

1.9

-2.1

III

-1.3

0.0

-1.3

IV

-2.2

-0.2

-2.0

2012

I

0.7

1.8

-1.1

II

-2.0

-0.6

-1.4

III

-1.9

-2.1

0.2

IV

-0.3

-2.0

1.6

2011

I

-1.4

-0.6

-0.8

II

-4.3

-4.6

0.4

III

3.6

5.4

-1.9

IV

-2.7

-1.7

-1.0

2010

I

1.9

3.3

-1.4

II

0.3

2.8

-2.5

III

0.7

1.7

-1.0

IV

-0.1

0.2

-0.3

2009

I

-4.8

-16.2

11.4

II

7.5

4.6

2.8

III

2.1

5.3

-3.2

IV

2.9

4.2

-1.3

2008

I

0.8

1.8

-1.0

II

0.4

-1.5

1.9

III

-0.1

0.1

-0.2

IV

-10.3

-9.3

-1.1

2007

I

1.0

1.6

-0.5

II

0.7

1.5

-0.8

III

2.2

1.7

0.5

IV

1.3

2.0

-0.7

Source: Japan Economic and Social Research Institute, Cabinet Office

http://www.esri.cao.go.jp/index-e.html

http://www.esri.cao.go.jp/en/sna/sokuhou/sokuhou_top.html

There was milder increase in Japan’s export corporate goods price index during the global recession in 2008 but similar sharp decline during the bank balance sheets effect in late 2008, as shown in Chart IV-5 of the Bank of Japan. Japan exports industrial goods whose prices have been less dynamic than those of commodities and raw materials. As a result, the export CGPI on the yen basis in Chart IV-5 trends down with oscillations after a brief rise in the final part of the recession in 2009. The export corporate goods price index on the yen basis fell from 93.9 in Jun 2009 to 84.1 in Jan 2012 or minus 10.4 percent and increased to 95.6 in Sep 2017 for gain of 13.7 percent relative to Jan 2012 and increase of 1.8 percent relative to Jun 2009. The choice of Jun 2009 is designed to capture the reversal of risk aversion beginning in Sep 2008 with the announcement of toxic assets in banks that would be withdrawn with the Troubled Asset Relief Program (TARP) (Cochrane and Zingales 2009). Reversal of risk aversion in the form of flight to the USD and obligations of the US government opened the way to renewed carry trades from zero interest rates to exposures in risk financial assets such as commodities. Japan exports industrial products and imports commodities and raw materials. The recovery from the global recession began in the third quarter of 2009.

Chart IV-5, Japan, Export Corporate Goods Price Index, Monthly, Yen Basis, 2008-2017

Source: Bank of Japan

http://www.stat-search.boj.or.jp/index_en.html

Chart IV-5A provides the export corporate goods price index on the basis of the contract currency. The export corporate goods price index on the basis of the contract currency increased from 105.9 in Jun 2009 to 111.5 in Apr 2012 or 5.3 percent but dropped to 100.6 in Sep 2017 or minus 9.8 percent relative to Apr 2012 and fell 5.0 percent to 100.6 in Sep 2017 relative to Jun 2009.

Chart IV-5A, Japan, Export Corporate Goods Price Index, Monthly, Contract Currency Basis, 2008-2017

Source: Bank of Japan

http://www.stat-search.boj.or.jp/index_en.html

Japan imports primary commodities and raw materials. As a result, the import corporate goods price index on the yen basis in Chart IV-6 shows an upward trend after declining from the increase during the global recession in 2008 driven by carry trades from fed funds rates. The index increases with carry trades from zero interest rates into commodity futures and declines during risk aversion from late 2008 into beginning of 2008 originating in doubts about soundness of US bank balance sheets. Measurement that is more careful should show that the terms of trade of Japan, export prices relative to import prices, declined during the commodity shocks originating in unconventional monetary policy. The decline of the terms of trade restricted potential growth of income in Japan (for the relation of terms of trade and growth see Pelaez 1979, 1976a). The import corporate goods price index on the yen basis increased from 82.4 in Jun 2009 to 99.6 in Apr 2012 or 20.9 percent and to 91.6 in Sep 2017 or decline of 8.0 percent relative to Apr 2012 and increase of 11.2 percent relative to Jun 2009.

Chart IV-6, Japan, Import Corporate Goods Price Index, Monthly, Yen Basis, 2008-2017

Source: Bank of Japan

http://www.stat-search.boj.or.jp/index_en.html

Chart IV-6A provides the import corporate goods price index on the contract currency basis. The import corporate goods price index on the basis of the contract currency increased from 95.0 in Jun 2009 to 131.6 in Apr 2012 or 38.5 percent and to 97.7 in Sep 2017 or minus 25.8 percent relative to Apr 2012 and increase of 2.8 percent relative to Jun 2009. There is evident deterioration of the terms of trade of Japan: the export corporate goods price index on the basis of the contract currency decreased 5.0 percent from Jun 2009 to Sep 2017 while the import corporate goods price index increased 2.8 percent. Prices of Japan’s exports of corporate goods, mostly industrial products, increased only 5.3 percent from Jun 2009 to Apr 2012, while imports of corporate goods, mostly commodities and raw materials increased 38.5 percent. Unconventional monetary policy induces carry trades from zero interest rates to exposures in commodities that squeeze economic activity of industrial countries by increases in prices of imported commodities and raw materials during periods without risk aversion. Reversals of carry trades during periods of risk aversion decrease prices of exported commodities and raw materials that squeeze economic activity in economies exporting commodities and raw materials. Devaluation of the dollar by unconventional monetary policy could increase US competitiveness in world markets but economic activity is squeezed by increases in prices of imported commodities and raw materials. Unconventional monetary policy causes instability worldwide instead of the mission of central banks of promoting financial and economic stability.

Chart IV-6A, Japan, Import Corporate Goods Price Index, Monthly, Contract Currency Basis, 2008-2017

Source: Bank of Japan

http://www.stat-search.boj.or.jp/index_en.html

Table IV-6B provides the Bank of Japan’s Corporate Goods Price indexes of exports and imports on the yen and contract bases from Jan 2008 to Sep 2017. There are oscillations of the indexes that are shown vividly in the four charts above. For the entire period from Jan 2008 to Sep 2017, the export index on the contract currency basis decreased 6.2 percent and decreased 7.5 percent on the yen basis. For the entire period from Jan 2008 to Sep 2017, the import price index decreased 11.9 percent on the contract currency basis and decreased 12.6 percent on the yen basis. During significant part of the expansion period, prices of Japan’s exports of corporate goods on the contract currency, mostly industrial products, increased only 5.3 percent from Jun 2009 to Apr 2012, while prices of imports of corporate goods on the contract currency, mostly commodities and raw materials, increased 38.5 percent. The charts show sharp deteriorations in relative prices of exports to prices of imports during multiple periods. Price margins of Japan’s producers are subject to periodic squeezes resulting from carry trades from zero interest rates of monetary policy to exposures in commodities.

Table IV-6B, Japan, Exports and Imports Corporate Goods Price Index, Contract Currency Basis and Yen Basis

X-CC

X-Y

M-CC

M-Y

2008/01

107.3

103.3

110.9

104.8

2008/02

107.9

103.9

112.8

106.2

2008/03

108.7

100.7

115.1

103.4

2008/04

109.9

103.2

121.3

110.3

2008/05

110.7

105

124.9

114.9

2008/06

111.9

108

131.6

123.6

2008/07

113.2

109.2

135

126.8

2008/08

112.1

109.2

135.6

129.5

2008/09

111

105.8

129

120.8

2008/10

108.3

98.1

120.2

107

2008/11

106.6

93.5

107.7

93.2

2008/12

105.9

90

98.4

81.9

2009/01

106

89

94.3

77.9

2009/02

105.4

89.6

94.4

79

2009/03

105.2

93.2

93.8

81.9

2009/04

105.5

94.5

93

81.9

2009/05

105.4

92.9

92.5

80

2009/06

105.9

93.9

95

82.4

2009/07

105.4

92.2

98.3

83.7

2009/08

106.3

93.4

98.7

84.4

2009/09

106.3

91.4

100.2

83.4

2009/10

106

90.5

100.2

82.8

2009/11

106.4

90.2

102.2

83.5

2009/12

106.3

90.1

105.1

85.9

2010/01

107.5

91.4

106.8

88.1

2010/02

107.8

90.9

107.5

87.9

2010/03

107.8

91.1

106.8

87.4

2010/04

108.7

93.6

110

92.1

2010/05

108.9

92.1

112

92.4

2010/06

108.2

90.9

110.2

90.1

2010/07

107.5

88.6

110

87.9

2010/08

107.2

87.1

109.6

85.9

2010/09

107.5

86.8

110.2

85.6

2010/10

108.2

86.3

110.7

84.4

2010/11

108.9

87.1

113

86.5

2010/12

109.4

88

115

88.6

2011/01

110.4

88.2

118.1

90.4

2011/02

111.3

89

120.1

91.9

2011/03

111.9

89.1

123.2

93.6

2011/04

112.6

91

127.7

98.6

2011/05

112.3

89.4

130.9

99

2011/06

112.2

88.8

129.4

97.3

2011/07

112

88

130.3

97.1

2011/08

112

86.4

130.6

95.2

2011/09

112.1

86

128.9

93.6

2011/10

111.4

85.2

128.4

93

2011/11

110.2

84.8

127.1

92.8

2011/12

109.7

84.6

127.9

93.6

2012/01

110.1

84.1

126.7

91.8

2012/02

110.7

85.7

127.6

93.7

2012/03

111.3

88.8

130.3

99.5

2012/04

111.5

88.3

131.6

99.6

2012/05

110.6

86.2

130.1

96.7

2012/06

109.6

85

126.9

94

2012/07

108.8

84.1

123.4

91.2

2012/08

109.1

84.2

123.8

91.3

2012/09

109.2

84.2

126.3

92.7

2012/10

109.3

84.7

125.4

92.7

2012/11

109.1

85.8

124.7

93.8

2012/12

108.9

87.7

124.9

96.5

2013/01

109.2

91.6

125.4

101.7

2013/02

109.7

94.8

126.5

105.9

2013/03

109.5

95.4

126.8

107.5

2013/04

108.3

96.2

125.7

109.1

2013/05

107.7

97.6

124

110.4

2013/06

107.3

94.9

123.4

106.8

2013/07

107.2

96.2

122.9

108.2

2013/08

107

94.9

123.2

106.9

2013/09

107

95.9

124.5

109.2

2013/10

107.3

95.5

124.6

108.3

2013/11

107.2

96.6

124.6

110

2013/12

107.2

98.8

125.4

113.6

2014/01

107.3

99

126

114.6

2014/02

106.9

97.7

125.4

112.5

2014/03

106.6

97.6

124.9

112.2

2014/04

106.3

97.5

124.1

111.8

2014/05

106.2

96.8

123.8

110.9

2014/06

105.9

96.7

123.9

111.2

2014/07

106

96.5

123.9

110.9

2014/08

106.1

97.3

123.7

111.6

2014/09

105.9

99.3

122.8

114

2014/10

105.2

99.1

120.7

112.7

2014/11

104.8

103.4

117.8

115.9

2014/12

103.8

104.1

113.8

114

2015/01

102.2

101.2

108.2

106.6

2015/02

101.2

100.1

102.1

100.7

2015/03

101.3

100.9

103.1

102.6

2015/04

101.1

100.2

102

101

2015/05

101.4

101.4

101.6

101.5

2015/06

101.3

102.9

102.5

104.3

2015/07

100.6

101.7

101.5

102.9

2015/08

99.8

100.9

99

100.4

2015/09

98.6

98.2

96.6

96.2

2015/10

97.9

97.3

95.5

95

2015/11

97.5

98

94.9

95.7

2015/12

97.1

97.3

92.9

93.2

2016/01

96.4

94.7

89.9

88.3

2016/02

95.9

92.8

87.5

84.4

2016/03

96.1

92.1

87.3

83.2

2016/04

96.5

91

88.2

82.4

2016/05

96.6

90.6

88.6

82.4

2016/06

96.5

88.8

89.9

81.6

2016/07

96.9

88.2

90.8

81.5

2016/08

96.9

87.1

90.7

79.9

2016/09

97

87.4

91.2

80.7

2016/10

97.5

88.6

91.1

81.6

2016/11

98.1

91.2

93.8

86.3

2016/12

98.7

95.5

93.7

90.6

2017/01

99.4

95.6

96

92.1

2017/02

99.8

95.3

97.5

92.5

2017/03

100.3

95.7

98.3

93.2

2017/04

99.9

93.8

98.2

91.3

2017/05

99.5

94.7

98

92.6

2017/06

99.3

94

97.1

91

2017/07

99.4

95.1

96.1

91.1

2017/08

100

94.6

96.5

90

2017/09

100.6

95.6

97.7

91.6

Note: X-CC: Exports Contract Currency; X-Y: Exports Yen; M-CC: Imports Contract; M-Y: Imports Yen

Source: Bank of Japan

http://www.stat-search.boj.or.jp/index_en.html

Japan also experienced sharp increase in inflation during the 1970s as in the episode of the Great Inflation in the US. Monetary policy focused on accommodating higher inflation, with emphasis solely on the mandate of promoting employment, has been blamed as deliberate or because of model error or imperfect measurement for creating the Great Inflation (http://cmpassocregulationblog.blogspot.com/2011/05/slowing-growth-global-inflation-great.html http://cmpassocregulationblog.blogspot.com/2011/04/new-economics-of-rose-garden-turned.html http://cmpassocregulationblog.blogspot.com/2011/03/is-there-second-act-of-us-great.html  and Appendix I The Great Inflation; see Taylor 1993, 1997, 1998LB, 1999, 2012FP, 2012Mar27, 2012Mar28, 2012JMCB and http://cmpassocregulationblog.blogspot.com/2017/01/rules-versus-discretionary-authorities.html and earlier http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html). A remarkable similarity with US experience is the sharp rise of the CGPI of Japan in 2008 driven by carry trades from policy interest rates rapidly falling to zero to exposures in commodity futures during a global recession. Japan had the same sharp waves of consumer price inflation during the 1970s as in the US (see Chart IV-5A and associated table at 10/01/17 (https://cmpassocregulationblog.blogspot.com/2017/10/destruction-of-household-nonfinancial.html https://cmpassocregulationblog.blogspot.com/2017/08/dollar-devaluation-and-interest-rate.html https://cmpassocregulationblog.blogspot.com/2017/07/data-dependent-monetary-policy-with_30.html https://cmpassocregulationblog.blogspot.com/2017/07/dollar-devaluation-and-rising-yields.html https://cmpassocregulationblog.blogspot.com/2017/05/mediocre-cyclical-united-states.html https://cmpassocregulationblog.blogspot.com/2017/04/dollar-devaluation-mediocre-cyclical.html https://cmpassocregulationblog.blogspot.com/2017/04/mediocre-cyclical-economic-growth-with.html https://cmpassocregulationblog.blogspot.com/2017/03/rising-valuations-of-risk-financial.html http://cmpassocregulationblog.blogspot.com/2017/01/rising-valuations-of-risk-financial.html http://cmpassocregulationblog.blogspot.com/2017/01/rules-versus-discretionary-authorities.html http://cmpassocregulationblog.blogspot.com/2016/11/dollar-revaluation-rising-yields-and.html http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states_30.html http://cmpassocregulationblog.blogspot.com/2016/10/mediocre-cyclical-united-states.html http://cmpassocregulationblog.blogspot.com/2016/08/and-as-ever-economic-outlook-is.html http://cmpassocregulationblog.blogspot.com/2016/07/business-fixed-investment-has-been-soft.html http://cmpassocregulationblog.blogspot.com/2016/07/financial-asset-values-rebound-from.html http://cmpassocregulationblog.blogspot.com/2016/05/appropriate-for-fed-to-increase.html http://cmpassocregulationblog.blogspot.com/2016/03/contraction-of-united-states-corporate.html http://cmpassocregulationblog.blogspot.com/2016/02/mediocre-cyclical-united-states.html http://cmpassocregulationblog.blogspot.com/2016/01/closely-monitoring-global-economic-and.html http://cmpassocregulationblog.blogspot.com/2015/12/dollar-revaluation-and-decreasing.html http://cmpassocregulationblog.blogspot.com/2015/11/dollar-revaluation-constraining.html http://cmpassocregulationblog.blogspot.com/2015/11/interest-rate-increase-considered.html http://cmpassocregulationblog.blogspot.com/2015/11/interest-rate-increase-considered.htmlhttp://cmpassocregulationblog.blogspot.com/2015/09/monetary-policy-designed-on-measurable.html

http://cmpassocregulationblog.blogspot.com/2015/08/fluctuations-of-global-financial.html http://cmpassocregulationblog.blogspot.com/2015/08/turbulence-of-valuations-of-financial_77.html http://cmpassocregulationblog.blogspot.com/2015/06/international-valuations-of-financial_29.html http://cmpassocregulationblog.blogspot.com/2015/06/dollar-revaluation-squeezing-corporate_97.html http://cmpassocregulationblog.blogspot.com/2015/05/dollar-devaluation-and-carry-trade.html http://cmpassocregulationblog.blogspot.com/2015/03/dollar-revaluation-and-financial-risk.html http://cmpassocregulationblog.blogspot.com/2015/03/irrational-exuberance-mediocre-cyclical.html http://cmpassocregulationblog.blogspot.com/2015/02/financial-and-international.html http://cmpassocregulationblog.blogspot.com/2014/12/valuations-of-risk-financial-assets.html http://cmpassocregulationblog.blogspot.com/2014/09/financial-volatility-mediocre-cyclical.html http://cmpassocregulationblog.blogspot.com/2014/09/geopolitical-and-financial-risks_71.html http://cmpassocregulationblog.blogspot.com/2014/03/financial-uncertainty-mediocre-cyclical_8145.html http://cmpassocregulationblog.blogspot.com/2014/03/financial-risks-slow-cyclical-united.html http://cmpassocregulationblog.blogspot.com/2014/02/mediocre-cyclical-united-states.html http://cmpassocregulationblog.blogspot.com/2013/12/collapse-of-united-states-dynamism-of.html http://cmpassocregulationblog.blogspot.com/2013/12/exit-risks-of-zero-interest-rates-world_1.html and earlier http://cmpassocregulationblog.blogspot.com/2013/10/twenty-eight-million-unemployed-or_561.html and at http://cmpassocregulationblog.blogspot.com/2013/09/increasing-interest-rate-risk_1.html http://cmpassocregulationblog.blogspot.com/2012/07/recovery-without-jobs-stagnating-real_09.html).

Chart IV-7, Japan, Domestic Corporate Goods Price Index, Monthly, 1960-2017

Source: Bank of Japan

http://www.stat-search.boj.or.jp/index_en.html

The producer price index of the US from 1970 to 2017 in Chart IV-8 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 IV-8, US, Producer Price Index Finished Goods, Monthly, 1960-2016

Source: US Bureau of Labor Statistics

http://www.bls.gov/ppi/

Further insight into inflation of the corporate goods price index (CGPI) of Japan is in Table IV-7. The increase in the tax on value added of consumption caused sharp increases in prices across all segments. Petroleum and coal with weight of 6.0 percent increased 1.1 percent in Sep 2017 and increased 13.7 percent in 12 months. Japan exports manufactured products and imports raw materials and commodities such that the country’s terms of trade, or export prices relative to import prices, deteriorate during commodity price increases. In contrast, prices of production machinery, with weight of 4.1 percent, decreased 0.2 percent in Sep 2017 and increased 0.1 percent in 12 months. In general, most manufactured products had been experiencing negative or low increases in prices while inflation rates have been high in 12 months for products originating in raw materials and commodities. The reversal of carry trades in commodity futures caused decrease in prices of commodities and raw materials while prices of manufactures stabilized. Ironically, unconventional monetary policy of zero interest rates and quantitative easing that intended to increase aggregate demand and GDP growth deteriorated the terms of trade of advanced economies with adverse effects on real income (for analysis of terms of trade and growth see Pelaez (1979, 1976a). There are now inflation effects of the intentional policy of devaluing the yen and recent collapse of commodity prices followed by increases.

Table IV-7, Japan, Corporate Goods Prices and Selected Components, % Weights, Month and 12 Months ∆%

Sep 2017

Weight

Month ∆%

12 Month ∆%

Total

1000.0

0.2

3.0

Food, Beverages

141.6

0.0

-0.2

Petroleum & Coal

59.5

1.1

13.7

Production Machinery

41.1

-0.2

0.1

Electronic Components

24.5

0.0

1.3

Electric Power, Gas & Water

67.1

0.2

10.7

Iron & Steel

51.7

0.4

11.9

Chemicals

89.2

0.3

3.3

Transport
Equipment

140.7

0.1

-0.3

Source: Bank of Japan

http://www.boj.or.jp/en/statistics/index.htm/

Percentage point contributions to change of the corporate goods price index (CGPI) in Sep 2017 are in Table IV-8, divided into domestic, export and import segments. In the domestic CGPI, increasing 0.2 percent in Sep 2017, the energy shock is evident in the contribution of 0.06 percentage points by petroleum and coal products in renewed carry trades of exposures in commodity futures. The exports CGPI increased 0.6 percent on the basis of the contract currency with contribution of 0.30 percentage points by chemicals and related products. The imports CGPI increased 1.2 percent on the contract currency basis. Petroleum, coal and natural gas contributed 0.93 percentage points. Shocks of risk aversion cause unwinding carry trades that result in declining commodity prices with resulting downward pressure on price indexes. The volatility of inflation adversely affects financial and economic decisions worldwide.

Table IV-8, Japan, Percentage Point Contributions to Change of Corporate Goods Price Index

Groups Sep 2017

Contribution to Change Percentage Points

A. Domestic Corporate Goods Price Index

Monthly Change: 
0.2%

Petroleum & Coal Products

0.06

Nonferrous Metals

0.05

Agriculture, Forestry & Fishery Products

0.04

Scrap & Waste

0.03

Chemicals & Related Products

0.03

Iron & Steel

0.02

Electric Power, Gas & Water

0.01

Pulp, Paper & Related Products

0.01

Electrical Machinery & Equipment

-0.01

B. Export Price Index

Monthly Change:   
0.6% contract currency

Chemicals & Related Products

0.30

Metals & Related Products

0.24

Other Primary Products & Manufactured Goods

0.09

Transportation Equipment

-0.02

Electric & Electronic Products

-0.02

C. Import Price Index

Monthly Change: 1.2% contract currency basis

Petroleum, Coal & Natural Gas

0.93

Metals & Related Products

0.20

Chemicals and Related Products

0.06

Beverages & Foods & Agriculture Products for Food

0.05

Electric & Electronic Products

-0.02

Source: Bank of Japan

http://www.boj.or.jp/en/statistics/index.htm/

There are two categories of responses in the Empire State Manufacturing Survey of the Federal Reserve Bank of New York (https://www.newyorkfed.org/survey/empire/empiresurvey_overview.html): current conditions and expectations for the next six months. There are responses in the survey for two types of prices: prices received or inputs of production and prices paid or sales prices of products. Table IV-5 provides indexes for the two categories and within them for the two types of prices from Jan 2011 to Oct 2017. The index of current prices paid or costs of inputs moved from 16.1 in Dec 2012 to 27.3 in Oct 2017 while the index of current prices received or sales prices moved from 1.1 in Dec 2012 to 7.0 in Oct 2017. The farther the index is from the area of no change at zero, the faster the rate of change. Prices paid or costs of inputs at 27.3 in Oct 2017 are expanding at faster pace than prices received or of sales of products at 7.0. The index of future prices paid or expectations of costs of inputs in the next six months fell from 51.6 in Dec 2012 to 41.4 in Oct 2017 while the index of future prices received or expectation of sales prices in the next six months decreased from 25.8 in Dec 2012 to 25.0 in Oct 2017. Prices paid or of inputs at 41.4 in Oct 2017 are expected to increase at a faster pace in the next six months than prices received or prices of sales products at 25.0 in Oct 2017. Prices of sales of finished products are less dynamic than prices of costs of inputs during waves of increases. Prices of costs of costs of inputs fall less rapidly than prices of sales of finished products during waves of price decreases. As a result, margins of prices of sales less costs of inputs oscillate with typical deterioration against producers, forcing companies to manage tightly costs and labor inputs. Instability of sales/costs margins discourages investment and hiring.

Table IV-5, US, FRBNY Empire State Manufacturing Survey, Diffusion Indexes, Prices Paid and Prices Received, SA

Current Prices Paid

Current Prices Received

Current Prices Paid

Current Prices Received

1/31/2011

35.8

15.8

60

42.1

2/28/2011

45.8

16.9

55.4

27.7

3/31/2011

53.2

20.8

71.4

36.4

4/30/2011

57.7

26.9

56.4

38.5

5/31/2011

69.9

28

68.8

35.5

6/30/2011

56.1

11.2

55.1

19.4

7/31/2011

43.3

5.6

51.1

30

8/31/2011

28.3

2.2

42.4

15.2

9/30/2011

32.6

8.7

53.3

22.8

10/31/2011

22.5

4.5

40.4

18

11/30/2011

18.3

6.1

36.6

25.6

12/31/2011

24.4

3.5

57

36

1/31/2012

26.4

23.1

53.8

30.8

2/29/2012

25.9

15.3

62.4

34.1

3/31/2012

50.6

13.6

66.7

32.1

4/30/2012

45.8

19.3

50.6

22.9

5/31/2012

37.3

12

57.8

22.9

6/30/2012

19.6

1

34

17.5

7/31/2012

7.4

3.7

35.8

16

8/31/2012

16.5

2.4

31.8

14.1

9/30/2012

19.1

5.3

40.4

23.4

10/31/2012

17.2

4.3

44.1

24.7

11/30/2012

14.6

5.6

39.3

15.7

12/31/2012

16.1

1.1

51.6

25.8

1/31/2013

22.6

10.8

38.7

21.5

2/28/2013

26.3

8.1

44.4

13.1

3/31/2013

25.8

2.2

50.5

23.7

4/30/2013

28.4

5.7

44.3

14.8

5/31/2013

20.5

4.5

29.5

14.8

6/30/2013

21

11.3

45.2

17.7

7/31/2013

17.4

1.1

28.3

12

8/31/2013

20.5

3.6

41

19.3

9/30/2013

21.5

8.6

39.8

24.7

10/31/2013

21.7

2.4

45.8

25.3

11/30/2013

17.1

-3.9

42.1

17.1

12/31/2013

15.7

3.6

48.2

27.7

1/31/2014

36.6

13.4

45.1

23.2

2/28/2014

25

15

40

23.8

3/31/2014

21.2

2.4

43.5

25.9

4/30/2014

22.4

10.2

33.7

14.3

5/31/2014

19.8

6.6

31.9

14.3

6/30/2014

17.2

4.3

36.6

16.1

7/31/2014

25

6.8

37.5

18.2

8/31/2014

27.3

8

42

21.6

9/30/2014

23.9

17.4

43.5

32.6

10/31/2014

11.4

6.8

42

26.1

11/30/2014

10.6

0

41.5

25.5

12/31/2014

10.4

6.3

40.6

32.3

1/31/2015

12.6

12.6

33.7

15.8

2/28/2015

14.6

3.4

27

5.6

3/31/2015

12.4

8.2

32

12.4

4/30/2015

19.1

4.3

38.3

13.8

5/31/2015

9.4

1

26

7.3

6/30/2015

9.6

1

24

5.8

7/31/2015

7.4

5.3

27.7

6.4

8/31/2015

7.3

0.9

34.5

10.9

9/30/2015

4.1

-5.2

28.9

7.2

10/31/2015

0.9

-8.5

27.4

7.5

11/30/2015

4.5

-4.5

29.1

11.8

12/31/2015

4

-4

27.3

20.2

1/31/2016

16

4

31

12

2/29/2016

3

-5

14.9

4

3/31/2016

3

-5.9

19.8

7.9

4/30/2016

19.2

2.9

27.9

5.8

5/31/2016

16.7

-3.1

28.1

6.3

6/30/2016

18.4

-1

29.6

7.1

7/31/2016

18.7

1.1

26.4

7.7

8/31/2016

15.5

2.1

25.8

9.3

9/30/2016

17

1.8

41.1

20.5

10/31/2016

22.6

4.7

35.8

30.2

11/30/2016

15.5

2.7

39.1

20.9

12/31/2016

22.6

3.5

42.6

22.6

1/31/2017

36.1

17.6

50.4

27.7

2/28/2017

37.8

19.4

38.8

25.5

3/31/2017

31

8.8

41.6

19.5

4/30/2017

32.8

12.4

37.2

25.5

5/31/2017

20.9

4.5

38.1

22.4

6/30/2017

20

10.8

33.1

13.8

7/31/2017

21.3

11

30.7

15.7

8/31/2017

31

6.2

33.3

21.7

9/30/2017

35.8

13.8

42.3

18.7

10/31/2017

27.3

7

41.4

25

Source: Federal Reserve Bank of New York

https://www.newyorkfed.org/survey/empire/empiresurvey_overview.html

Price indexes of the Federal Reserve Bank of Philadelphia Outlook Survey are in Table IV-5A. As in inflation waves throughout the world (Section I and earlier https://cmpassocregulationblog.blogspot.com/2017/09/dollar-devaluation-world-inflation.html) indexes of both current and expectations of future prices paid and received were quite high until May 2011. Prices paid, or inputs, were more dynamic, reflecting carry trades from zero interest rates to commodity futures. All indexes softened after May 2011 with even decline of prices received in Aug 2011 during the first round of risk aversion. Current and future price indexes have increased again but not back to the intensity in the beginning of 2011 because of risk aversion frustrating carry trades even induced by zero interest rates. The index of prices paid or prices of inputs moved from 20.6 in Dec 2012 to 38.1 in Oct 2017. The index of current prices received was minus 2.2 in Apr 2013, indicating decrease of prices received. The index of current prices received decreased from 9.1 in Dec 2012 to minus 5.7 in Sep 2015, decreasing to minus 4.8 in Feb 2016. The index of current prices received was 14.2 in Oct 2017. The farther the index is from the area of no change at zero, the faster the rate of change. The index of current prices paid or costs of inputs at 38.1 in Oct 2017 indicates faster expansion than the index of current prices received or sales prices of production in Oct 2017, showing 14.2. Prices paid indicate faster expansion than prices received during most of the history of the index. The index of future prices paid increased to 60.2 in Oct 2017 from 42.1 in Dec 2012 while the index of future prices received increased from 21.7 in Dec 2012 to 41.1 in Oct 2017. Expectations are incorporating faster increases in prices of inputs or costs of production, 60.2 in Oct 2017, than of sales prices of produced goods, 41.1 in Oct 2017, forcing companies to manage tightly costs and labor inputs. Volatility of margins of sales/costs discourages investment and hiring.

Table IV-5A, US, Federal Reserve Bank of Philadelphia Business Outlook Survey, Current and Future Prices Paid and Prices Received, SA

Current Prices Paid

Current Prices Received

Future Prices Paid

Future Prices Received

Dec-10

42.7

5.3

56.2

24.2

Jan-11

48.2

12.6

59

34.6

Feb-11

61.4

13.7

69.1

31.6

Mar-11

59.2

17.9

61.5

33.5

Apr-11

52.8

22.9

56.4

36.3

May-11

51.2

20.6

54.8

28.4

Jun-11

36

6.4

40.7

6.8

Jul-11

34.1

5.6

47.8

17.3

Aug-11

23.6

-3.4

42.6

22.8

Sep-11

30.1

6.4

38.1

20.4

Oct-11

22.7

1.6

41.3

27.8

Nov-11

21.8

5.2

34.4

26.4

Dec-11

24.9

5.6

42.7

21.1

Jan-12

26.1

9.2

48.1

21.9

Feb-12

33.3

10.4

52.5

26.4

Mar-12

17.6

6.9

38.7

24.8

Apr-12

21.9

9.7

37

25.1

May-12

10.2

1.1

39.9

9

Jun-12

1.2

-5.9

32.7

16.8

Jul-12

8.1

3.3

26.8

20.6

Aug-12

16.3

6.6

34.7

23.9

Sep-12

12.9

2.7

38.1

24.6

Oct-12

17.3

4.6

44.1

15.2

Nov-12

22.2

4.7

45.8

10.7

Dec-12

20.6

9.1

42.1

21.7

Jan-13

13

0.8

35.4

21.8

Feb-13

12.7

0.2

36.9

23.1

Mar-13

13.8

1.3

35.2

20.5

Apr-13

11.7

-2.2

31.2

16.7

May-13

12.6

0.5

34.5

19

Jun-13

17.2

11.8

29.4

23.9

Jul-13

18.9

5.6

39.6

25

Aug-13

17.9

12.6

33.6

23.4

Sep-13

22.1

11.5

37.1

26.8

Oct-13

17.4

8.9

41.4

34.5

Nov-13

23.3

6.5

41

36.3

Dec-13

16.5

8.8

40.6

28.2

Jan-14

20.4

8.6

38.2

13.8

Feb-14

16.1

9.7

31.1

19.6

Mar-14

22.6

7.5

33.9

20.7

Apr-14

21.3

10.8

38.2

21.1

May-14

26.7

17.2

37.7

28.9

Jun-14

26.6

10.5

41.9

29.4

Jul-14

29.8

13.9

35.9

21.8

Aug-14

21.5

5.8

44

28.6

Sep-14

21.7

7.5

38.7

25.3

Oct-14

23.6

16.9

31

21.7

Nov-14

14.2

8

32.7

18.4

Dec-14

14.4

11.1

26.1

20.1

Jan-15

12.3

3

31.6

21.1

Feb-15

6

2.3

37.4

22.3

Mar-15

3.4

-4.6

30.8

10.2

Apr-15

1.7

-2

19.6

13.6

May-15

-14.1

-7.1

22.3

19

Jun-15

10.4

1.4

38

11.5

Jul-15

16.6

0.3

32.9

15.9

Aug-15

2.8

-3.7

33.5

9.9

Sep-15

-2.8

-5.7

24.7

4.1

Oct-15

-1.7

-1.2

17.7

8.7

Nov-15

-7

-3.4

23.6

10.5

Dec-15

-9.5

-6.8

25.5

13.8

Jan-16

-1.2

-2.2

20.4

11.5

Feb-16

-2.8

-4.8

16.4

4.1

Mar-16

1.5

2.9

25.1

15.3

Apr-16

13.7

6.1

35.3

21.4

May-16

13.5

11.5

23.9

12.5

Jun-16

21.2

4.1

34.4

17.1

Jul-16

11.9

1.3

27.4

22.3

Aug-16

18.7

6.6

29.7

15.5

Sep-16

20.8

9.4

39.8

31.2

Oct-16

8.9

-1.9

41.5

27.9

Nov-16

27.6

16.4

38.3

30.6

Dec-16

28.1

8

46.5

29.1

Jan-17

32.5

26.8

49

27.5

Feb-17

29.9

10.6

51.1

23.5

Mar-17

40.7

20.6

55.7

40.2

Apr-17

33.7

16.6

34.7

28.6

May-17

24.2

15.3

42.7

22.9

Jun-17

23.6

20.6

40.9

28.7

Jul-17

19.1

9

46.6

29.7

Aug-17

21.1

13.5

34.8

40.4

Sep-17

34.4

22.8

46.2

31.7

Oct-17

38.1

14.2

60.2

41.1

Source: Federal Reserve Bank of Philadelphia

https://www.philadelphiafed.org/

Chart IV-1 of the Business Outlook Survey of the Federal Reserve Bank of Philadelphia Outlook Survey provides the diffusion index of current prices paid or prices of inputs from 2006 to 2017. Recession dates are in shaded areas. In the middle of deep global contraction after IVQ2007, input prices continued to increase in speculative carry trades from central bank policy rates falling toward zero into commodities futures. The index peaked above 70 in the second half of 2008. Inflation of inputs moderated significantly during the shock of risk aversion in late 2008, even falling briefly into contraction territory below zero during several months in 2009 in the flight away from risk financial assets into US government securities (Cochrane and Zingales 2009) that unwound carry trades. Return of risk appetite induced carry trade with significant increase until return of risk aversion in the first round of the European sovereign debt crisis in Apr 2010. Carry trades returned during risk appetite in expectation that the European sovereign debt crisis was resolved. The various inflation waves originating in carry trades induced by zero interest rates with alternating episodes of risk aversion are mirrored in the prices of inputs after 2011, in particular after Aug 2012 with the announcement of the Outright Monetary Transactions Program of the European Central Bank (http://www.ecb.int/press/pr/date/2012/html/pr120906_1.en.html). Subsequent risk aversion and flows of capital away from commodities into stocks and high-yield bonds caused sharp decline in the index of prices paid followed by another recent rebound with marginal decline and new increase. The index falls, rebounds and falls again in the final segment but there are no episodes of contraction after 2009 with exception of minus 14.1 in May 2015, minus 2.8 in Sep 2015, minus 1.7 in Oct 2015, minus 7.0 in Nov 2015 and minus 9.5 in Dec 2015. The reading for the index in Jan 2016 is minus 1.2 and minus 2.8 for Feb 2016. The index is 1.5 in Mar 2016 and 13.7 in Apr 2016, increasing at 13.5 in May 2016 and 21.2 in Jun 2016. The index reached 11.9 in Jul 2016, 18.7 in Aug 2016 and 20.8 in Sep 2016. The index was 8.9 in Oct 2016 and 38.1 in Oct 2017.

Chart IV-1, Federal Reserve Bank of Philadelphia Business Outlook Survey Current Prices Paid Diffusion Index SA

Source: Federal Reserve Bank of Philadelphia

https://www.philadelphiafed.org/

Chart IV-2 of the Federal Reserve Bank of Philadelphia Outlook Survey provides the diffusion index of current prices received from 2006 to 2017. The significant difference between the index of current prices paid in Chart IV-1 and the index of current prices received in Chart IV-2 is that increases in prices paid are significantly sharper than increases in prices received. There were several periods of negative readings of prices received from 2010 to 2016. Prices paid increased at 3.4 in Mar 2015 while prices received contracted at 4.6. There were several contractions of prices paid: 14.1 in May 2015 with milder contraction of 7.1 of prices received; minus 2.8 for prices paid in Sep 2015 with minus 5.7 for prices received; and minus 1.7 for prices paid in Oct 2015 with minus 1.2 for prices received. The index of prices received fell to minus 7.0 in Nov 2015 with minus 3.4 for prices paid and to minus 9.5 in Dec 2015 with minus 6.8 for prices paid. The index of prices received fell to minus 4.8 in Feb 2016 with minus 2.8 for prices paid. The index of prices paid increased at 1.5 in Mar 2016 with 2.9 for prices received. Prices paid moved to 38.1 in Oct 2017 while prices received moved to 14.2. Prices received relative to prices paid deteriorate most of the time largely because of the carry trades from zero interest rates to commodity futures. Profit margins of business are compressed intermittently by fluctuations of commodity prices induced by unconventional monetary policy of zero interest rates, frustrating production, investment and hiring decisions of business, which is precisely the opposite outcome pursued by unconventional monetary policy.

Chart IV-2, Federal Reserve Bank of Philadelphia Business Outlook Survey Current Prices Received Diffusion Index SA

Source: Federal Reserve Bank of Philadelphia

https://www.philadelphiafed.org/

Chart IV-2A of the Federal Reserve Bank of Philadelphia shows current prices paid and current prices received from Jan 2007 to Mar 2017. Current prices paid jumped ahead of current prices received during the contraction from IVQ2007 to IIQ2009 through the carry trade from zero interest rates to exposures in commodity derivatives. There is the same behavior during most of the cyclical expansion after IIIQ2009. Rebalancing of financial investment portfolios away from commodities into equities explains the recent weakness of prices paid. There is a new ongoing carry trade into commodity futures.

Chart IV-2A, Federal Reserve Bank of Philadelphia Business Outlook Survey Current Prices Paid and Current Prices Received Diffusion Index SA

Source: Federal Reserve Bank of Philadelphia

https://www.philadelphiafed.org/

Chart IV-2B of the Federal Reserve Bank of Philadelphia shows the six-month forecast and current prices received of the Business Outlook Survey from 2007 to Jun 2017. There is correlation in the direction of the indexes. The six-month forecast is typically above current prices received. There is upward trend in both indexes in the final segment with wide fluctuations.

Chart IV-2B, Federal Reserve Bank of Philadelphia Business Outlook Survey Current Prices Received and Future Prices Received Diffusion Index SA

Source: Federal Reserve Bank of Philadelphia

https://www.philadelphiafed.org/

Chart IV-2C of the Federal Reserve Bank of Philadelphia shows the six-month forecast and current prices received of the Business Outlook Survey from 2007 to Jul 2017. There is correlation in the direction of the indexes. The six-month forecast is typically above current prices received. There is upward trend in both indexes in the final segment with wide fluctuations.

Chart IV-2c, Federal Reserve Bank of Philadelphia Business Outlook Survey Current Prices Received and Future Prices Received Diffusion Index SA

Source: Federal Reserve Bank of Philadelphia

https://www.philadelphiafed.org/

Chart IV-2D of the Federal Reserve Bank of Philadelphia shows the six-month forecast and current prices received of the Business Outlook Survey from 2007 to Sep 2017. There is correlation in the direction of the indexes. The six-month forecast is typically above current prices received. There is upward trend in both indexes in the final segment with wide fluctuations.

Chart IV-2d, Federal Reserve Bank of Philadelphia Business Outlook Survey Current Prices Received and Future Prices Received Diffusion Index SA

Source: Federal Reserve Bank of Philadelphia

https://www.philadelphiafed.org/

Chart IV-2DE of the Federal Reserve Bank of Philadelphia shows the six-month forecast and current prices received of the Business Outlook Survey from 2007 to Oct 2017. There is correlation in the direction of the indexes. The six-month forecast is typically above current prices received. There is upward trend in both indexes in the final segment with wide fluctuations.

Chart IV-2de, Federal Reserve Bank of Philadelphia Business Outlook Survey Current Prices Received and Future Prices Received Diffusion Index SA

Source: Federal Reserve Bank of Philadelphia

https://www.philadelphiafed.org/

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

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