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FOMC Increases Interest Rates with Probable Two More Increases in 2018, United States Inflation, Rules, Discretionary Authorities and Slow Productivity Growth, Collapse of United States Dynamism of Income Growth and Employment Creation in the Lost Economic Cycle of the Global Recession with Economic Growth Underperforming Below Trend Worldwide, World Cyclical Slow Growth and Global Recession Risk
© Carlos M. Pelaez, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018
I United States Inflation
IIC Rules, Discretionary Authorities and Slow Productivity Growth
II IB Collapse of United States Dynamism of Income Growth and Employment Creation in the Lost Economic Cycle of the Global Recession with Economic Growth Underperforming Below Trend Worldwide
III World Financial Turbulence
IV Global Inflation
V World Economic Slowdown
VA United States
VB Japan
VC China
VD Euro Area
VE Germany
VF France
VG Italy
VH United Kingdom
VI Valuation of Risk Financial Assets
VII Economic Indicators
VIII Interest Rates
IX Conclusion
References
Appendixes
Appendix I The Great Inflation
IIIB Appendix on Safe Haven Currencies
IIIC Appendix on Fiscal Compact
IIID Appendix on European Central Bank Large Scale Lender of Last Resort
IIIG Appendix on Deficit Financing of Growth and the Debt Crisis
IC United States Inflation. IC Long-Term Inflation. Key percentage average yearly rates of the US economy on growth and inflation are provided in Table I-1 updated with release of new data. The choice of dates prevents the measurement of long-term potential economic growth because of two recessions from IQ2001 (Mar) to IVQ2001 (Nov) with decline of GDP of 0.3 percent and the drop in GDP of 4.2 percent in the recession from IVQ2007 (Dec) to IIQ2009 (June) (https://cmpassocregulationblog.blogspot.com/2018/06/stronger-dollar-mediocre-cyclical.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/dollar-appreciation-mediocre-cyclical.html). Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. Key percentage average yearly rates of the US economy on growth and inflation are provided in Table I-1 updated with release of new data. US economic growth has been at only 2.2 percent on average in the cyclical expansion in the 35 quarters from IIIQ2009 to IQ2018. 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 second estimate of GDP for IQ2018 (https://www.bea.gov/newsreleases/national/gdp/2018/pdf/gdp1q18_2nd.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/2018/06/stronger-dollar-mediocre-cyclical.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/dollar-appreciation-mediocre-cyclical.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, 3.8 percent from IQ1983 to IQ1991, 3.8 percent from IQ1983 to IIQ1991, 3.8 percent from IQ1983 to IIIQ1991 and at 7.8 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2018/06/stronger-dollar-mediocre-cyclical.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/dollar-appreciation-mediocre-cyclical.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 IQ2018 would have accumulated to 35.4 percent. GDP in IQ2018 would be $20,298.9 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2919.2 billion than actual $17,379.7 billion. There are about two trillion dollars of GDP less than at trend, explaining the 20.6 million unemployed or underemployed equivalent to actual unemployment/underemployment of 12.1 percent of the effective labor force (https://cmpassocregulationblog.blogspot.com/2018/06/twenty-one-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2018/05/twenty-one-million-unemployed-or.html). US GDP in IQ2018 is 14.4 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $17,379.7 billion in IQ2018 or 15.9 percent at the average annual equivalent rate of 1.5 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.2 percent per year from Apr 1919 to Apr 2018. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 108.3221 in Dec 2007 to 154.7937 in Apr 2018. The actual index NSA in Apr 2018 is 104.3625, which is 32.6 percent below trend. Manufacturing output grew at average 2.0 percent between Dec 1986 and Apr 2018. Using trend growth of 2.0 percent per year, the index would increase to 135.5768 in Apr 2018. The output of manufacturing at 104.3625 in Apr 2018 is 23.0 percent below trend under this alternative calculation. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. In the period from 1929 to 2017 the average growth rate of real GDP was 3.2 percent and 3.2 percent between 1947 to 2017, which is close to 3.0 percent from 1870 to 2010 measured by Lucas (2011May), as shown in Table I-1. From 1929 to 2017, nominal GDP grew at the average rate of 6.1 percent and at 6.4 percent from 1947 to 2017. The implicit deflator increased at the average rate of 2.8 percent from 1929 to 2017 and at 3.2 percent from 1947 to 2017. Between 2000 and 2017, real GDP grew at the average rate of 1.8 percent per year, nominal GDP at 3.8 percent and the implicit deflator at 1.9 percent. The annual average rate of CPI increase was 3.1 percent from 1913 to 2017, 3.5 percent from 1947 to 2017 and 2.1 percent from 2000 to 2017. Between 2000 and 2017, the average rate of CPI inflation was 2.1 percent per year and 2.0 percent excluding food and energy. From 2000 to 2018, the average rate of CPI inflation was 2.3 percent and 2.0 percent excluding food and energy. The average annual rate of PPI inflation was 2.9 percent from 1947 to 2017 and 2.1 percent from 2000 to 2017. PPI inflation increased at 2.1 percent per year on average from 2000 to 2017, 2.3 percent on average from 2000 to 2018 and at 1.8 percent excluding food and energy from 2000 to 2017 and 1.8 percent from 2000 to 2018. Producer price inflation of finished energy goods increased at average 3.2 percent between 2000 and 2017 and at 3.8 percent between 2000 and 2018. There is also inflation in international trade. Import prices increased at 1.3 percent per year between 2000 and 2017 and 1.4 percent between 2000 and 2018. The commodity price shock is revealed by inflation of import prices of petroleum increasing at 4.2 percent per year between 2000 and 2017 and at 5.6 percent between 2000 and 2018. Import prices excluding petroleum increased at the average rate of 0.7 percent from 2000 to 2017 and at 0.7 percent from 2000 to 2018. The average percentage rates of increase of import prices excluding fuels are at 1.0 percent for 2002 to 2017 and 1.1 percent for 2002 to 2018. Export prices rose at the average rate of 1.2 percent between 2000 and 2017 and at 1.4 percent from 2000 to 2018. What spared the US of sharper decade-long deterioration of the terms of trade, (export prices)/(import prices), was its diversification and competitiveness in agriculture. Agricultural export prices grew at the average yearly rate of 3.3 percent from 2000 to 2017 and at 3.4 percent from 2000 to 2018. US nonagricultural export prices rose at 0.9 percent per year from 2000 to 2017 and at 1.2 percent from 2000 to 2018. The share of petroleum imports in US trade far exceeds that of agricultural exports. Unconventional monetary policy inducing carry trades in commodities has deteriorated US terms of trade, prices of exports relative to prices of imports, tending to restrict growth of US aggregate real income. These dynamic inflation rates are not similar to those for the economy of Japan where inflation was negative in seven of the 10 years in the 2000s. There is no reality of the proposition of need of unconventional monetary policy in the US because of deflation panic. There is reality in cyclical slow economic growth currently but not in secular stagnation.
Table I-1, US, Average Growth Rates of Real and Nominal GDP, Consumer Price Index, Producer Price Index and Import and Export Prices, Percent per Year
| Real GDP | 2000-2017: 1.8% 1929-2017: 3.2% 1947-2017: 3.2% |
| Nominal GDP | 2000-2017: 3.8% 1929-2017: 6.1% 1947-2017: 6.4% |
| Implicit Price Deflator | 2000-2017: 1.9% 1929-2017: 2.8% 1947-2017: 3.2% |
| CPI | 2000-2017: 2.1% Annual 1913-2017: 3.1% 1947-2017: 3.5% 2000-2017: 2.1% |
| CPI ex Food and Energy | 2000-2017: 2.0% |
| PPI | 2000-2017: 2.1% Annual 1947-2017: 2.9% 2000-2017: 2.1% |
| PPI ex Food and Energy | 2000-2017: 1.8% |
| PPI Finished Energy Goods | 2000-2017: 3.2% 2000-2018: 3.8% |
| Import Prices | 2000-2017: 1.3% |
| Import Prices of Petroleum and Petroleum Products | 2000-2017: 4.2% |
| Import Prices Excluding Petroleum | 2000-2017: 0.7% |
| Import Prices Excluding Fuels | 2002-2017: 1.0% |
| Export Prices | 2000-2017: 1.2% |
| Agricultural Export Prices | 2000-2017: 3.3% |
| Nonagricultural Export Prices | 2000-2017: 0.9% |
Note: rates for price indexes in the row beginning with “CPI” and ending in the row “Nonagricultural Export Prices” are for May 2000 to May 2017 and for May 2000 to May 2018.
Sources: https://www.bea.gov/iTable/index_nipa.cfm https://www.bls.gov/ppi/ https://www.bls.gov/cpi/data.htm https://www.bls.gov/mxp/data.htm
ID Current US Inflation. Unconventional monetary policy of zero interest rates and large-scale purchases of long-term securities for the balance sheet of the central bank is proposed to prevent deflation. The data of CPI inflation of all goods and CPI inflation excluding food and energy for the past six decades does not show even one negative change, as shown in Table CPIEX.
Table CPIEX, Annual Percentage Changes of the CPI All Items Excluding Food and Energy
| Year | Annual ∆% |
| 1958 | 2.4 |
| 1959 | 2.0 |
| 1960 | 1.3 |
| 1961 | 1.3 |
| 1962 | 1.3 |
| 1963 | 1.3 |
| 1964 | 1.6 |
| 1965 | 1.2 |
| 1966 | 2.4 |
| 1967 | 3.6 |
| 1968 | 4.6 |
| 1969 | 5.8 |
| 1970 | 6.3 |
| 1971 | 4.7 |
| 1972 | 3.0 |
| 1973 | 3.6 |
| 1974 | 8.3 |
| 1975 | 9.1 |
| 1976 | 6.5 |
| 1977 | 6.3 |
| 1978 | 7.4 |
| 1979 | 9.8 |
| 1980 | 12.4 |
| 1981 | 10.4 |
| 1982 | 7.4 |
| 1983 | 4.0 |
| 1984 | 5.0 |
| 1985 | 4.3 |
| 1986 | 4.0 |
| 1987 | 4.1 |
| 1988 | 4.4 |
| 1989 | 4.5 |
| 1990 | 5.0 |
| 1991 | 4.9 |
| 1992 | 3.7 |
| 1993 | 3.3 |
| 1994 | 2.8 |
| 1995 | 3.0 |
| 1996 | 2.7 |
| 1997 | 2.4 |
| 1998 | 2.3 |
| 1999 | 2.1 |
| 2000 | 2.4 |
| 2001 | 2.6 |
| 2002 | 2.4 |
| 2003 | 1.4 |
| 2004 | 1.8 |
| 2005 | 2.2 |
| 2006 | 2.5 |
| 2007 | 2.3 |
| 2008 | 2.3 |
| 2009 | 1.7 |
| 2010 | 1.0 |
| 2011 | 1.7 |
| 2012 | 2.1 |
| 2013 | 1.8 |
| 2014 | 1.7 |
| 2015 | 1.8 |
| 2016 | 2.2 |
| 2017 | 1.8 |
Source: Bureau of Labor Statistics
The history of producer price inflation in the past five decades does not provide evidence of deflation. The finished core PPI does not register even one single year of decline, as shown in Table PPIEX.
Table PPIEX, Annual Percentage Changes of the PPI Finished Goods Excluding Food and Energy
| Year | Annual ∆% |
| 1974 | 11.4 |
| 1975 | 11.4 |
| 1976 | 5.7 |
| 1977 | 6.0 |
| 1978 | 7.5 |
| 1979 | 8.9 |
| 1980 | 11.2 |
| 1981 | 8.6 |
| 1982 | 5.7 |
| 1983 | 3.0 |
| 1984 | 2.4 |
| 1985 | 2.5 |
| 1986 | 2.3 |
| 1987 | 2.4 |
| 1988 | 3.3 |
| 1989 | 4.4 |
| 1990 | 3.7 |
| 1991 | 3.6 |
| 1992 | 2.4 |
| 1993 | 1.2 |
| 1994 | 1.0 |
| 1995 | 2.1 |
| 1996 | 1.4 |
| 1997 | 0.3 |
| 1998 | 0.9 |
| 1999 | 1.7 |
| 2000 | 1.3 |
| 2001 | 1.4 |
| 2002 | 0.1 |
| 2003 | 0.2 |
| 2004 | 1.5 |
| 2005 | 2.4 |
| 2006 | 1.5 |
| 2007 | 1.9 |
| 2008 | 3.4 |
| 2009 | 2.6 |
| 2010 | 1.2 |
| 2011 | 2.4 |
| 2012 | 2.6 |
| 2013 | 1.5 |
| 2014 | 1.9 |
| 2015 | 2.0 |
| 2016 | 1.6 |
| 2017 | 1.8 |
Source: Bureau of Labor Statistics
Chart I-1 provides US nominal GDP from 1929 to 2017. The chart disguises the decline of nominal GDP during the 1930s from $104.6 billion in 1929 to $57.2 billion in 1933 or by 45.3 percent (data from the US Bureau of Economic Analysis at http://www.bea.gov/iTable/index_nipa.cfm). The level of nominal GDP reached $102.9 billion in 1940 and exceeded the $104.6 billion of 1929 only with $129.4 billion in 1941. The only major visible bump in the chart occurred in the recession of IVQ2007 to IIQ2009 with revised cumulative decline of real GDP of 4.2 percent. US nominal GDP fell from $14,718.6 billion in 2008 to $14,418.7 billion in 2009 or by 2.0 percent. US nominal GDP rose to $14,964.4 billion in 2010 or by 3.8 percent and to $15,517.9 billion in 2011 for an additional 3.7 percent for cumulative increase of 7.6 percent relative to 2009 and to $16,155.3 billion in 2012 for an additional 4.1 percent and cumulative increase of 12.0 percent relative to 2009. US nominal GDP increased from $14,477.6 in 2007 to $19,390.6 billion in 2017 or by 33.9 percent at the average annual rate of 3.0 percent per year (http://www.bea.gov/iTable/index_nipa.cfm). Tendency for deflation would be reflected in persistent bumps. In contrast, during the Great Depression in the four years of 1929 to 1933, GDP in constant dollars fell 26.3 percent cumulatively and fell 45.3 percent in current dollars (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 150-2, Pelaez and Pelaez, Globalization and the State, Vol. II (2009b), 205-7). The comparison of the global recession after 2007 with the Great Depression is entirely misleading (https://cmpassocregulationblog.blogspot.com/2018/06/stronger-dollar-mediocre-cyclical.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/dollar-appreciation-mediocre-cyclical.html).
Chart I-1, US, Nominal GDP 1929-2017
Source: US Bureau of Economic Analysis
http://www.bea.gov/iTable/index_nipa.cfm
Chart I-2 provides US real GDP from 1929 to 2017. The chart also disguises the Depression of the 1930s. In the four years of 1929 to 1933, GDP in constant dollars fell 26.3 percent cumulatively and fell 45.3 percent in current dollars (Pelaez and Pelaez, Financial Regulation after the Global Recession (2009a), 150-2, Pelaez and Pelaez, Globalization and the State, Vol. II (2009b), 205-7; data from the US Bureau of Economic Analysis at http://www.bea.gov/iTable/index_nipa.cfm). Persistent deflation threatening real economic activity would also be reflected in the series of long-term growth of real GDP. There is no such behavior in Chart I-2 except for periodic recessions in the US economy that have occurred throughout history.
Chart I-2, US, Real GDP 1929-2017
Source: US Bureau of Economic Analysis
http://www.bea.gov/iTable/index_nipa.cfm
Deflation would also be in evidence in long-term series of prices in the form of bumps. The GDP implicit deflator series in Chart I-3 from 1929 to 2017 shows sharp dynamic behavior over time. There is decline of the implicit price deflator of GDP by 25.8 percent from 1929 to 1933 (data from the US Bureau of Economic Analysis at http://www.bea.gov/iTable/index_nipa.cfm). In contrast, the implicit price deflator of GDP of the US increased from 97.337 (2009 =100) in 2007 to 100.00 in 2009 or by 2.7 percent and increased to 113.421 in 2017 or by 13.4 percent relative to 2009 and 16.5 percent relative to 2007. The implicit price deflator of US GDP increased in every quarter from IVQ2007 to IVQ2012 with only two declines from 100.062 in IQ2009 to 99.895 in IIQ2009 or by 0.2 percent and to 99.873 in IIIQ2009 for cumulative 0.2 percent relative to IQ2009 and -0.02 percent relative to IIQ2009 (http://www.bea.gov/iTable/index_nipa.cfm). Wars are characterized by rapidly rising prices followed by declines when peace is restored. The US economy is not plagued by deflation but by long-run inflation.
Chart I-3, US, GDP Implicit Price Deflator 1929-2017
Source: US Bureau of Economic Analysis
http://www.bea.gov/iTable/index_nipa.cfm
Chart I-4 provides percent change from preceding quarter in prices of GDP at seasonally adjusted annual rates (SAAR) from 1980 to 2018. There is one case of negative change by 0.6 percent in IIQ2009 that was adjustment from 2.8 percent in IIIQ2008 following 2.3 percent in IQ2008 and 1.8 percent IIQ2008 caused by carry trades from policy interest rates being moved to zero into commodity futures. These positions were reversed because of the fear of toxic assets in banks in the proposal of TARP in late 2008 (Cochrane and Zingales 2009). Prices of GDP increased at 0.6 percent in IVQ2014. GDP prices decreased at 0.1 percent in IQ2015, increasing at 2.2 percent in IIQ015 and at 1.4 percent in IIIQ2015. Prices of GDP increased at 0.8 percent in IVQ2015 and at 0.3 percent in IQ2016. Prices of GDP increased at 2.4 percent in IIQ2016 and increased at 1.4 percent in IIIQ2016. Prices of GDP increased at 2.0 percent in IVQ2016 and increased at 2.0 percent in IQ2017. Prices of GDP increased at 1.0 percent in IIQ2017 and increased at 2.1 percent in IIIQ2017. Prices of GDP increased at 2.3 percent in IVQ2017 and increased at 1.9 percent in IQ2018. There has not been actual deflation or risk of deflation threatening depression in the US that would justify unconventional monetary policy.
Chart I-4, Percent Change from Preceding Period in Prices for GDP Seasonally Adjusted at Annual Rates 1980-2018
Source: US Bureau of Economic Analysis
http://www.bea.gov/iTable/index_nipa.cfm
Chart I-5 provides percent change from preceding year in prices of GDP from 1929 to 2017. There are four consecutive years of declines of prices of GDP during the Great Depression: 3.8 percent in 1930, 9.9 percent in 1931, 11.4 percent in 1932 and 2.7 percent in 1933. There were two consecutive declines of 1.8 percent in 1938 and 1.3 percent in 1939. Prices of GDP fell 0.1 percent in 1949 after increasing 12.6 percent in 1946, 11.2 percent in 1947 and 5.6 percent in 1948, which is similar to experience with wars in other countries. There are no other negative changes of annual prices of GDP in 74 years from 1939 to 2017.
Chart I-5, Percent Change from Preceding Year in Prices for Gross Domestic Product 1930-2017
http://www.bea.gov/iTable/index_nipa.cfm
The producer price index of the US from 1947 to 2018 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, 1947-2018
Source: US Bureau of Labor Statistics
Chart I-17 provides 12-month percentage changes of the producer price index from 1948 to 2018. 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 2018.
Chart I-7, US, Producer Price Index, Finished Goods, 12-Month Percentage Change, NSA, 1948-2018
Source: US Bureau of Labor Statistics
Annual percentage changes of the producer price index from 1948 to 2017 are shown in Table I-1A. The producer price index fell 2.8 percent in 1949 following the adjustment to World War II and fell 0.6 percent in 1952 and 1.0 percent in 1953 around the Korean War. There are two other mild declines of 0.3 percent in 1959 and 0.3 percent in 1963. There are only few subsequent and isolated declines of the producer price index of 1.4 percent in 1986, 0.8 percent in 1998, 1.3 percent in 2002 and 2.6 percent in 2009. The decline of 2009 was caused by unwinding of carry trades in 2008 that had lifted oil prices to $140/barrel during deep global recession because of the panic of probable toxic assets in banks that would be removed with the Troubled Asset Relief Program (TARP) (Cochrane and Zingales 2009). Producer prices fell 3.2 percent in 2015 and declined 1.0 percent in 2016 during collapse of commodity prices form high prices induced by zero interest rates. Producer prices increased 3.2 percent in 2017. There is no evidence in this history of 66 years of the US producer price index suggesting that there is frequent and persistent deflation shock requiring aggressive unconventional monetary policy. The design of such anti-deflation policy could provoke price and financial instability because of lags in effect of monetary policy, model errors, inaccurate forecasts and misleading analysis of current economic conditions.
Table I-1A, US, Annual PPI Inflation ∆% 1948-2017
| Year | Annual ∆% |
| 1948 | 8.0 |
| 1949 | -2.8 |
| 1950 | 1.8 |
| 1951 | 9.2 |
| 1952 | -0.6 |
| 1953 | -1.0 |
| 1954 | 0.3 |
| 1955 | 0.3 |
| 1956 | 2.6 |
| 1957 | 3.8 |
| 1958 | 2.2 |
| 1959 | -0.3 |
| 1960 | 0.9 |
| 1961 | 0.0 |
| 1962 | 0.3 |
| 1963 | -0.3 |
| 1964 | 0.3 |
| 1965 | 1.8 |
| 1966 | 3.2 |
| 1967 | 1.1 |
| 1968 | 2.8 |
| 1969 | 3.8 |
| 1970 | 3.4 |
| 1971 | 3.1 |
| 1972 | 3.2 |
| 1973 | 9.1 |
| 1974 | 15.4 |
| 1975 | 10.6 |
| 1976 | 4.5 |
| 1977 | 6.4 |
| 1978 | 7.9 |
| 1979 | 11.2 |
| 1980 | 13.4 |
| 1981 | 9.2 |
| 1982 | 4.1 |
| 1983 | 1.6 |
| 1984 | 2.1 |
| 1985 | 1.0 |
| 1986 | -1.4 |
| 1987 | 2.1 |
| 1988 | 2.5 |
| 1989 | 5.2 |
| 1990 | 4.9 |
| 1991 | 2.1 |
| 1992 | 1.2 |
| 1993 | 1.2 |
| 1994 | 0.6 |
| 1995 | 1.9 |
| 1996 | 2.7 |
| 1997 | 0.4 |
| 1998 | -0.8 |
| 1999 | 1.8 |
| 2000 | 3.8 |
| 2001 | 2.0 |
| 2002 | -1.3 |
| 2003 | 3.2 |
| 2004 | 3.6 |
| 2005 | 4.8 |
| 2006 | 3.0 |
| 2007 | 3.9 |
| 2008 | 6.3 |
| 2009 | -2.6 |
| 2010 | 4.2 |
| 2011 | 6.1 |
| 2012 | 1.9 |
| 2013 | 1.2 |
| 2014 | 1.9 |
| 2015 | -3.2 |
| 2016 | -1.0 |
| 2017 | 3.2 |
Source: US Bureau of Labor Statistics
The producer price index excluding food and energy from 1973 to 2018, the first historical date of availability in the dataset of the Bureau of Labor Statistics (BLS), shows similarly dynamic behavior as the overall index, as shown in Chart I-8. There is no evidence of persistent deflation in the US PPI.
Chart I-8, US Producer Price Index, Finished Goods Excluding Food and Energy, NSA, 1973-2018
Source: US Bureau of Labor Statistics
Chart I-9 provides 12-month percentage rates of change of the finished goods index excluding food and energy. The dominating characteristic is the Great Inflation of the 1970s. The double hump illustrates how inflation may appear to be subdued and then returns with strength.
Chart I-9, US Producer Price Index, Finished Goods Excluding Food and Energy, 12-Month Percentage Change, NSA, 1974-2018
Source: US Bureau of Labor Statistics
The producer price index of energy goods from 1974 to 2018 is in Chart I-10. The first jump occurred during the Great Inflation of the 1970s analyzed in various comments of this blog (http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html 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 in Appendix I. There is relative stability of producer prices after 1986 with another jump and decline in the late 1990s into the early 2000s. The episode of commodity price increases during a global recession in 2008 could only have occurred with interest rates dropping toward zero, which stimulated the carry trade from zero interest rates to leveraged positions in commodity futures. Commodity futures exposures were dropped in the flight to government securities after Sep 2008. Commodity future exposures were created again when risk aversion diminished around Mar 2010 after the finding that US bank balance sheets did not have the toxic assets that were mentioned in proposing TARP in Congress (see Cochrane and Zingales 2009). Fluctuations in commodity prices and other risk financial assets originate in carry trade when risk aversion ameliorates. There are also fluctuations originating in shifts in preference for asset classes such as between commodities and equities.
Chart I-10, US, Producer Price Index, Finished Energy Goods, NSA, 1974-2018
Source: US Bureau of Labor Statistics
Chart I-11 shows 12-month percentage changes of the producer price index of finished energy goods from 1975 to 2018. This index is only available after 1974 and captures only one of the humps of energy prices during the Great Inflation. Fluctuations in energy prices have occurred throughout history in the US but without provoking deflation. Two cases are the decline of oil prices in 2001 to 2002 that has been analyzed by Barsky and Kilian (2004) and the collapse of oil prices from over $140/barrel with shock of risk aversion to the carry trade in Sep 2008.
Chart I-11, US, Producer Price Index, Finished Energy Goods, 12-Month Percentage Change, NSA, 1974-2018
Source: US Bureau of Labor Statistics
http://www.bls.gov/cpi/data.htm
Chart I-12 provides the consumer price index NSA from 1918 to 2018. 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, 1918-2018
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 2018. 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 1918-2018
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 2017. There have been only cases of annual declines of the CPI after wars:
- World War I minus 10.5 percent in 1921 and minus 6.1 percent in 1922 following cumulative increases of 83.5 percent in four years from 1917 to 1920 at the average of 16.4 percent per year
- World War II: minus 1.2 percent in 1949 following cumulative 33.9 percent in three years from 1946 to 1948 at average 10.2 percent per year
- Minus 0.4 percent in 1955 two years after the end of the Korean War
- Minus 0.4 percent in 2009.
- The decline of 0.4 percent in 2009 followed increase of 3.8 percent in 2008 and is explained by the reversal of speculative carry trades into commodity futures that were created in 2008 as monetary policy rates were driven to zero. The reversal occurred after misleading statement on toxic assets in banks in the proposal for TARP (Cochrane and Zingales 2009).
There were declines of 1.7 percent in both 1927 and 1928 during the episode of revival of rules of the gold standard. The only persistent deflationary period since 1914 was during the Great Depression in the years from 1930 to 1933 and again in 1938-1939. Consumer prices increased only 0.1 percent in 2015 because of the collapse of commodity prices from artificially high levels induced by zero interest rates. Consumer prices increased 1.3 percent in 2016, increasing at 2.1 percent in 2017. 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 ∆% 1914-2017
| Year | Annual ∆% |
| 1914 | 1.0 |
| 1915 | 1.0 |
| 1916 | 7.9 |
| 1917 | 17.4 |
| 1918 | 18.0 |
| 1919 | 14.6 |
| 1920 | 15.6 |
| 1921 | -10.5 |
| 1922 | -6.1 |
| 1923 | 1.8 |
| 1924 | 0.0 |
| 1925 | 2.3 |
| 1926 | 1.1 |
| 1927 | -1.7 |
| 1928 | -1.7 |
| 1929 | 0.0 |
| 1930 | -2.3 |
| 1931 | -9.0 |
| 1932 | -9.9 |
| 1933 | -5.1 |
| 1934 | 3.1 |
| 1935 | 2.2 |
| 1936 | 1.5 |
| 1937 | 3.6 |
| 1938 | -2.1 |
| 1939 | -1.4 |
| 1940 | 0.7 |
| 1941 | 5.0 |
| 1942 | 10.9 |
| 1943 | 6.1 |
| 1944 | 1.7 |
| 1945 | 2.3 |
| 1946 | 8.3 |
| 1947 | 14.4 |
| 1948 | 8.1 |
| 1949 | -1.2 |
| 1950 | 1.3 |
| 1951 | 7.9 |
| 1952 | 1.9 |
| 1953 | 0.8 |
| 1954 | 0.7 |
| 1955 | -0.4 |
| 1956 | 1.5 |
| 1957 | 3.3 |
| 1958 | 2.8 |
| 1959 | 0.7 |
| 1960 | 1.7 |
| 1961 | 1.0 |
| 1962 | 1.0 |
| 1963 | 1.3 |
| 1964 | 1.3 |
| 1965 | 1.6 |
| 1966 | 2.9 |
| 1967 | 3.1 |
| 1968 | 4.2 |
| 1969 | 5.5 |
| 1970 | 5.7 |
| 1971 | 4.4 |
| 1972 | 3.2 |
| 1973 | 6.2 |
| 1974 | 11.0 |
| 1975 | 9.1 |
| 1976 | 5.8 |
| 1977 | 6.5 |
| 1978 | 7.6 |
| 1979 | 11.3 |
| 1980 | 13.5 |
| 1981 | 10.3 |
| 1982 | 6.2 |
| 1983 | 3.2 |
| 1984 | 4.3 |
| 1985 | 3.6 |
| 1986 | 1.9 |
| 1987 | 3.6 |
| 1988 | 4.1 |
| 1989 | 4.8 |
| 1990 | 5.4 |
| 1991 | 4.2 |
| 1992 | 3.0 |
| 1993 | 3.0 |
| 1994 | 2.6 |
| 1995 | 2.8 |
| 1996 | 3.0 |
| 1997 | 2.3 |
| 1998 | 1.6 |
| 1999 | 2.2 |
| 2000 | 3.4 |
| 2001 | 2.8 |
| 2002 | 1.6 |
| 2003 | 2.3 |
| 2004 | 2.7 |
| 2005 | 3.4 |
| 2006 | 3.2 |
| 2007 | 2.8 |
| 2008 | 3.8 |
| 2009 | -0.4 |
| 2010 | 1.6 |
| 2011 | 3.2 |
| 2012 | 2.1 |
| 2013 | 1.5 |
| 2014 | 1.6 |
| 2015 | 0.1 |
| 2016 | 1.3 |
| 2017 | 2.1 |
Source: US Bureau of Labor Statistics http://www.bls.gov/cpi/data.htm
Chart I-14 provides the consumer price index excluding food and energy from 1957 to 2018. There is long-term inflation in the US without episodes of persistent deflation.
Chart I-14, US, Consumer Price Index Excluding Food and Energy, NSA, 1957-2018
Source: US Bureau of Labor Statistics http://www.bls.gov/cpi/data.htm
Chart I-15 provides 12-month percentage changes of the consumer price index excluding food and energy from 1958 to 2018. There are three waves of inflation in the 1970s during the Great Inflation. There is no episode of deflation.
Chart I-15, US, Consumer Price Index Excluding Food and Energy, 12-Month Percentage Change, NSA, 1958-2018
Source: US Bureau of Labor Statistics http://www.bls.gov/cpi/data.htm
The consumer price index of housing is in Chart I-16. There was also acceleration during the Great Inflation of the 1970s. The index flattens after the global recession in IVQ2007 to IIQ2009. Housing prices collapsed under the weight of construction of several times more housing than needed. Surplus housing originated in subsidies and artificially low interest rates in the shock of unconventional monetary policy in 2003 to 2004 in fear of deflation.
Chart I-16, US, Consumer Price Index Housing, NSA, 1967-2017
Source: US Bureau of Labor Statistics http://www.bls.gov/cpi/data.htm
Chart I-17 provides 12-month percentage changes of the housing CPI. The Great Inflation also had extremely high rates of housing inflation. Housing is considered as potential hedge of inflation.
Chart I-17, US, Consumer Price Index, Housing, 12- Month Percentage Change, NSA, 1968-2017
Source: US Bureau of Labor Statistics http://www.bls.gov/cpi/data.htm
ID Current US Inflation. Consumer price inflation has fluctuated in recent months. Table I-3 provides 12-month consumer price inflation in May 2018 and annual equivalent percentage changes for the months from Mar 2018 to May 2018 of the CPI and major segments. The final column provides inflation from Apr 2018 to May 2018. CPI inflation increased 2.8 percent in the 12 months ending in May 2018. The annual equivalent rate from Mar 2018 to Mar 2018 was 1.2 percent in the new episode of reversal and renewed positions of carry trades from zero interest rates to commodities exposures; and the monthly inflation rate of 0.2 percent annualizes at 2.4 percent with oscillating carry trades at the margin. These inflation rates fluctuate in accordance with inducement of risk appetite or frustration by risk aversion of carry trades from zero interest rates to commodity futures. At the margin, the decline in commodity prices in sharp recent risk aversion in commodities markets caused lower inflation worldwide (with return in some countries in Dec 2012 and Jan-Feb 2013) that followed a jump in Aug-Sep 2012 because of the relaxed risk aversion resulting from the bond-buying program of the European Central Bank or Outright Monetary Transactions (OMT) (http://www.ecb.int/press/pr/date/2012/html/pr120906_1.en.html). Carry trades moved away from commodities into stocks with resulting weaker commodity prices and stronger equity valuations. There is reversal of exposures in commodities but with preferences of equities by investors. Geopolitical events in Eastern Europe and the Middle East together with economic conditions worldwide are inducing risk concerns in commodities at the margin. With zero or very low interest rates, commodity prices would increase again in an environment of risk appetite, as shown in past oscillating inflation. Excluding food and energy, core CPI inflation was 2.2 percent in the 12 months ending in May 2018 and 2.0 percent in annual equivalent from Mar 2018 to May 2018. There is no deflation in the US economy that could justify further unconventional monetary policy, which is now open-ended or forever with very low interest rates and cessation of bond-buying by the central bank but with reinvestment of interest and principal, or QE→∞ even if the economy grows back to potential. The FOMC is engaging in gradual reduction of the Fed balance sheet. Financial repression of very low interest rates is now intended as a permanent distortion of resource allocation by clouding risk/return decisions, preventing the economy from expanding along its optimal growth path. The FOMC is initiating reduction of the positions in securities held outright in the Fed’s balance sheet. Consumer food prices in the US increased 1.2 percent in 12 months ending in May 2018 and increased at 1.6 percent in annual equivalent from Mar 2018 to May 2018. Monetary policies stimulating carry trades of commodities futures that increase prices of food constitute a highly regressive tax on lower income families for whom food is a major portion of the consumption basket especially with wage increases below inflation in a recovery without hiring (https://cmpassocregulationblog.blogspot.com/2018/06/twenty-one-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2018/05/recovery-without-hiring-ten-million.html). Energy consumer prices increased 11.7 percent in 12 months, decreased at 2.2 percent in annual equivalent from Mar 2018 to May 2018 and increased 0.9 percent in May 2018 or at 11.4 percent in annual equivalent. Waves of inflation are induced by carry trades from zero interest rates to commodity futures, which are unwound and repositioned during alternating risk aversion and risk appetite originating in the European debt crisis and increasingly in growth, soaring debt and politics in China. For lower income families, food and energy are a major part of the family budget. Inflation is not persistently low or threatening deflation in annual equivalent in any of the categories in Table I-2 but simply reflecting waves of inflation originating in carry trades. Zero interest rates induce carry trades into commodity futures positions with episodes of risk aversion and portfolio reallocations causing fluctuations that determine an upward trend of prices.
Table I-3, US, Consumer Price Index Percentage Changes 12 months NSA and Annual Equivalent ∆%
| % RI | ∆% 12 Months May 2018/May | ∆% Annual Equivalent Mar 2018 to May 2018 SA | ∆% May 2018/Apr 2018 SA | |
| CPI All Items | 100.000 | 2.8 | 1.2 | 0.2 |
| CPI ex Food and Energy | 79.898 | 2.2 | 2.0 | 0.2 |
| Food | 13.273 | 1.2 | 1.6 | 0.0 |
| Food at Home | 7.311 | 0.1 | 0.8 | -0.2 |
| Food Away from Home | 5.962 | 2.7 | 2.4 | 0.3 |
| Energy | 7.830 | 11.7 | -2.2 | 0.9 |
| Gasoline | 4.181 | 21.8 | -1.5 | 1.7 |
| Electricity | 2.596 | 1.0 | -2.0 | 0.1 |
| Commodities less Food and Energy | 19.870 | -0.3 | -1.2 | -0.1 |
| New Vehicles | 3.732 | -1.1 | -0.8 | 0.3 |
| Used Cars and Trucks | 2.420 | -1.7 | -10.7 | -0.9 |
| Medical Care Commodities | 1.722 | 2.7 | 4.9 | 1.3 |
| Apparel | 3.185 | 1.4 | -1.2 | 0.0 |
| Services Less Energy Services | 59.027 | 3.0 | 3.2 | 0.3 |
| Shelter | 32.715 | 3.5 | 4.1 | 0.3 |
| Rent of Primary Residence | 7.768 | 3.6 | 4.1 | 0.3 |
| Owner’s Equivalent Rent of Residences | 23.584 | 3.4 | 3.2 | 0.2 |
| Transportation Services | 5.975 | 3.8 | -0.8 | 0.0 |
| Medical Care Services | 6.923 | 2.3 | 2.4 | -0.` |
% RI: Percent Relative Importance
Source: US Bureau of Labor Statistics http://www.bls.gov/cpi/
Table I-4 provides weights of components in the consumer price of the US in Dec 2012. Housing has a weight of 41.021 percent. The combined weight of housing and transportation is 57.867 percent or more than one-half of consumer expenditures of all urban consumers. The combined weight of housing, transportation and food and beverages is 73.128 percent of the US CPI. Table I-3 provides relative importance of key items in May 2018.
Table I-4, US, Relative Importance, 2009-2010 Weights, of Components in the Consumer Price Index, US City Average, Dec 2012
| All Items | 100.000 |
| Food and Beverages | 15.261 |
| Food | 14.312 |
| Food at home | 8.898 |
| Food away from home | 5.713 |
| Housing | 41.021 |
| Shelter | 31.681 |
| Rent of primary residence | 6.545 |
| Owners’ equivalent rent | 22.622 |
| Apparel | 3.564 |
| Transportation | 16.846 |
| Private Transportation | 15.657 |
| New vehicles | 3.189 |
| Used cars and trucks | 1.844 |
| Motor fuel | 5.462 |
| Gasoline | 5.274 |
| Medical Care | 7.163 |
| Medical care commodities | 1.714 |
| Medical care services | 5.448 |
| Recreation | 5.990 |
| Education and Communication | 6.779 |
| Other Goods and Services | 3.376 |
Refers to all urban consumers, covering approximately 87 percent of the US population (see http://www.bls.gov/cpi/cpiovrvw.htm#item1). Source: US Bureau of Labor Statistics http://www.bls.gov/cpi/cpiri2011.pdf http://www.bls.gov/cpi/cpiriar.htm http://www.bls.gov/cpi/cpiri2012.pdf
Chart I-18 provides the US consumer price index for housing from 2001 to 2018. Housing prices rose sharply during the decade until the bump of the global recession and increased again in 2011-2012 with some stabilization in 2013. There is renewed increase in 2014 followed by stabilization and renewed increase in 2015-2018. The CPI excluding housing would likely show much higher inflation. The commodity carry trades resulting from unconventional monetary policy have compressed income remaining after paying for indispensable shelter.
Chart I-18, US, Consumer Price Index, Housing, NSA, 2001-2018
Source: US Bureau of Labor Statistics http://www.bls.gov/cpi/data.htm
Chart I-19 provides 12-month percentage changes of the housing CPI. Percentage changes collapsed during the global recession but have been rising into positive territory in 2011 and 2012-2013 but with the rate declining and then increasing into 2014. There is decrease into 2015 followed by stability and marginal increase in 2016-18.
Chart I-19, US, Consumer Price Index, Housing, 12-Month Percentage Change, NSA, 2001-2018
Source: US Bureau of Labor Statistics
http://www.bls.gov/cpi/data.htm
There have been waves of consumer price inflation in the US in 2011 and into 2018 (https://cmpassocregulationblog.blogspot.com/2018/05/dollar-strengthening-world-inflation.htm and earlier https://cmpassocregulationblog.blogspot.com/2018/04/rising-yields-world-inflation-waves.html) that are illustrated in Table I-5. The first wave occurred in Jan-Apr 2011 and was caused by the carry trade of commodity prices induced by unconventional monetary policy of zero interest rates. Cheap money at zero opportunity cost in environment of risk appetite was channeled into financial risk assets, causing increases in commodity prices. The annual equivalent rate of increase of the all-items CPI in Jan-Apr 2011 was 4.9 percent and the CPI excluding food and energy increased at annual equivalent rate of 1.8 percent. The second wave occurred during the collapse of the carry trade from zero interest rates to exposures in commodity futures because of risk aversion in financial markets created by the sovereign debt crisis in Europe. The annual equivalent rate of increase of the all-items CPI dropped to 1.8 percent in May-Jun 2011 while the annual equivalent rate of the CPI excluding food and energy increased at 2.4 percent. In the third wave in Jul-Sep 2011, annual equivalent CPI inflation rose to 3.2 percent while the core CPI increased at 2.4 percent. The fourth wave occurred in the form of increase of the CPI all-items annual equivalent rate to 1.8 percent in Oct-Nov 2011 with the annual equivalent rate of the CPI excluding food and energy remaining at 2.4 percent. The fifth wave occurred in Dec 2011 to Jan 2012 with annual equivalent headline inflation of 1.8 percent and core inflation of 2.4 percent. In the sixth wave, headline CPI inflation increased at annual equivalent 2.4 percent in Feb-Apr 2012 and 2.0 percent for the core CPI. The seventh wave in May-Jul occurred with annual equivalent inflation of minus 1.2 percent for the headline CPI in May-Jul 2012 and 2.0 percent for the core CPI. The eighth wave is with annual equivalent inflation of 6.8 percent in Aug-Sep 2012 but 5.7 percent including Oct. In the ninth wave, annual equivalent inflation in Nov 2012 was minus 2.4 percent under the new shock of risk aversion and 0.0 percent in Dec 2012 with annual equivalent of 0.0 percent in Nov 2012-Jan 2013 and 2.0 percent for the core CPI. In the tenth wave, annual equivalent of the headline CPI was 6.2 percent in Feb 2013 and 1.2 percent for the core CPI. In the eleventh wave, annual equivalent was minus 3.0 percent in Mar-Apr 2013 and 0.6 percent for the core index. In the twelfth wave, annual equivalent inflation was 1.4 percent in May-Sep 2013 and 2.2 percent for the core CPI. In the thirteenth wave, annual equivalent CPI inflation in Oct-Nov 2013 was 1.8 percent and 1.8 percent for the core CPI. Inflation returned in the fourteenth wave at 2.7 percent for the headline CPI index and 1.8 percent for the core CPI in annual equivalent for Dec 2013 to Mar 2014. In the fifteenth wave, inflation moved to annual equivalent 1.8 percent for the headline index in Apr-Jul 2014 and 2.1 percent for the core index. In the sixteenth wave, annual equivalent inflation was 0.0 percent in Aug 2014 and 1.2 percent for the core index. In the seventeenth wave, annual equivalent inflation was 0.0 percent for the headline CPI and 2.4 percent for the core in Sep-Oct 2014. In the eighteenth wave, annual equivalent inflation was minus 4.3 percent for the headline index in Nov 2014-Jan 2015 and 1.2 percent for the core. In the nineteenth wave, annual equivalent inflation was 2.9 percent for the headline index and 2.2 percent for the core index in Feb-Jun 2015. In the twentieth wave, annual equivalent inflation was at 2.4 percent in Jul 2015 for the headline and core indexes. In the twenty-first wave, consumer prices decreased at 1.2 percent in annual equivalent in Aug-Sep 2015. In the twenty-second wave, consumer prices increased at annual equivalent 1.2 percent for the central index and 2.4 percent for the core in Oct-Nov 2015. In the twenty-third wave, annual equivalent inflation was 0.0 percent for the headline CPI in Dec 2015 to Jan 2016 and 1.8 percent for the core. In the twenty-fourth wave, annual equivalent was minus 2.4 percent and 2.4 percent for the core in Feb 2016. In the twenty-fifth wave, annual equivalent inflation was at 3.0 percent for the central index in Mar-Apr 2016 and at 1.8 percent for the core index. In the twenty-sixth wave, annual equivalent inflation was 3.0 percent for the central CPI in May-Jun 2016 and 2.4 percent for the core CPI. In the twenty-seventh wave, annual equivalent inflation was 0.0 percent for the central CPI and 2.4 percent for the core in Jul 2016. In the twenty-eighth wave, annual equivalent inflation was 2.4 percent for the headline CPI in Aug 2016 and 2.4 percent for the core. In the twenty-ninth wave, CPI prices increased at annual equivalent 3.0 percent in Sep-Oct 2016 while the core CPI increased at 1.2 percent. In the thirtieth wave, annual equivalent CPI prices increased at 3.0 percent in Nov-Dec 2016 while the core CPI increased at 2.4 percent. In the thirty-first wave, CPI prices increased at annual equivalent 6.2 percent in Jan 2017 while the core index increased at 3.7 percent. In the thirty-second wave, CPI prices changed at annual equivalent 0.0 percent in Feb 2017 while the core increased at 2.4 percent. In the thirty-third wave, CPI prices decreased at annual equivalent 2.4 percent in Mar 2017 while the core index fell at 1.2 percent. In the thirty-fourth wave, CPI prices increased at 2.4 percent annual equivalent in Apr 2017 while the core index increased at 1.2 percent. In the thirty-fifth wave, CPI prices fell at annual equivalent 0.6 in May-Jun 2017 while core prices increased at 1.2 percent. In the thirty-sixth wave, CPI prices increased at annual equivalent 1.2 percent in Jul 2017 while core prices increased at 1.2 percent. In the thirty-seventh wave, CPI prices increased at annual equivalent 5.5 percent in Aug-Sep 2017 while core prices increased at 1.8 percent. In the thirty-eighth wave, CPI prices increased at 2.4 percent annual equivalent in Oct-Nov 2017 while core prices increased at 1.8 percent. In the thirty-ninth wave, CPI prices increased at 3.7 percent annual equivalent in Dec 2017-Feb 2018 while core prices increased at 3.0 percent. In the fortieth wave, CPI prices decreased at 1.2 percent annual equivalent in Mar 2018 while core prices increased at 2.4 percent. In the forty-first wave, CPI prices increased at 2.4 percent annual equivalent in Apr-May 2018 while core prices increased at 1.8 percent. The conclusion is that inflation accelerates and decelerates in unpredictable fashion because of shocks or risk aversion and portfolio reallocations in carry trades from zero interest rates to commodity derivatives.
Table I-5, US, Headline and Core CPI Inflation Monthly SA and 12 Months NSA ∆%
| All Items SA Month | All Items NSA 12 month | Core SA | Core NSA | |
| May 2018 | 0.2 | 2.8 | 0.2 | 2.2 |
| Apr | 0.2 | 2.5 | 0.1 | 2.1 |
| AE ∆% Apr-May | 2.4 | 1.2 | ||
| Mar | -0.1 | 2.4 | 0.2 | 2.1 |
| AE ∆% Mar | -1.2 | 2.4 | ||
| Feb | 0.2 | 2.2 | 0.2 | 1.8 |
| Jan | 0.5 | 2.1 | 0.3 | 1.8 |
| Dec 2017 | 0.2 | 2.1 | 0.2 | 1.8 |
| AE ∆% Dec-Feb | 3.7 | 3.0 | ||
| Nov | 0.3 | 2.2 | 0.1 | 1.7 |
| Oct | 0.1 | 2.0 | 0.2 | 1.8 |
| AE ∆% Oct-Nov | 2.4 | 1.8 | ||
| Sep | 0.5 | 2.2 | 0.1 | 1.7 |
| Aug | 0.4 | 1.9 | 0.2 | 1.7 |
| AE ∆% Aug-Sep | 5.5 | 1.8 | ||
| Jul | 0.1 | 1.7 | 0.1 | 1.7 |
| AE ∆% Jul | 1.2 | 1.2 | ||
| Jun | 0.0 | 1.6 | 0.1 | 1.7 |
| May | -0.1 | 1.9 | 0.1 | 1.7 |
| AE ∆% May-Jun | -0.6 | 1.2 | ||
| Apr | 0.2 | 2.2 | 0.1 | 1.9 |
| AE ∆% Apr | 2.4 | 1.2 | ||
| Mar | -0.2 | 2.4 | -0.1 | 2.0 |
| AE ∆% Mar | -2.4 | -1.2 | ||
| Feb | 0.0 | 2.7 | 0.2 | 2.2 |
| AE ∆% Feb | 0.0 | 2.4 | ||
| Jan | 0.5 | 2.5 | 0.3 | 2.3 |
| AE ∆% Jan | 6.2 | 3.7 | ||
| Dec 2016 | 0.3 | 2.1 | 0.2 | 2.2 |
| Nov | 0.2 | 1.7 | 0.2 | 2.1 |
| AE ∆% Nov-Dec | 3.0 | 2.4 | ||
| Oct | 0.3 | 1.6 | 0.1 | 2.1 |
| Sep | 0.2 | 1.5 | 0.1 | 2.2 |
| AE ∆% Sep-Oct | 3.0 | 1.2 | ||
| Aug | 0.2 | 1.1 | 0.2 | 2.3 |
| AE ∆ Aug | 2.4 | 2.4 | ||
| Jul | 0.0 | 0.8 | 0.2 | 2.2 |
| AE ∆% Jul | 0.0 | 2.4 | ||
| Jun | 0.3 | 1.0 | 0.2 | 2.2 |
| May | 0.2 | 1.0 | 0.2 | 2.2 |
| AE ∆% May-Jun | 3.0 | 2.4 | ||
| Apr | 0.3 | 1.1 | 0.2 | 2.1 |
| Mar | 0.2 | 0.9 | 0.1 | 2.2 |
| AE ∆% Mar-Apr | 3.0 | 1.8 | ||
| Feb | -0.2 | 1.0 | 0.2 | 2.3 |
| AE ∆% Feb | -2.4 | 2.4 | ||
| Jan | 0.1 | 1.4 | 0.2 | 2.2 |
| Dec 2015 | -0.1 | 0.7 | 0.1 | 2.1 |
| AE ∆% Dec-Jan | 0.0 | 1.8 | ||
| Nov | 0.1 | 0.5 | 0.2 | 2.0 |
| Oct | 0.1 | 0.2 | 0.2 | 1.9 |
| AE ∆% Oct-Nov | 1.2 | 2.4 | ||
| Sep | -0.2 | 0.0 | 0.2 | 1.9 |
| Aug | 0.0 | 0.2 | 0.1 | 1.8 |
| AE ∆% Aug-Sep | -1.2 | 1.8 | ||
| Jul | 0.2 | 0.2 | 0.2 | 1.8 |
| AE ∆% Jul | 2.4 | 2.4 | ||
| Jun | 0.3 | 0.1 | 0.2 | 1.8 |
| May | 0.3 | 0.0 | 0.1 | 1.7 |
| Apr | 0.1 | -0.2 | 0.2 | 1.8 |
| Mar | 0.3 | -0.1 | 0.3 | 1.8 |
| Feb | 0.2 | 0.0 | 0.1 | 1.7 |
| AE ∆% Feb-Jun | 2.9 | 2.2 | ||
| Jan | -0.6 | -0.1 | 0.1 | 1.6 |
| Dec 2014 | -0.3 | 0.8 | 0.1 | 1.6 |
| Nov | -0.2 | 1.3 | 0.1 | 1.7 |
| AE ∆% Nov-Jan | -4.3 | 1.2 | ||
| Oct | 0.0 | 1.7 | 0.2 | 1.8 |
| Sep | 0.0 | 1.7 | 0.2 | 1.7 |
| AE ∆% Sep-Oct | 0.0 | 2.4 | ||
| Aug | 0.0 | 1.7 | 0.1 | 1.7 |
| AE ∆% Aug | 0.0 | 1.2 | ||
| Jul | 0.1 | 2.0 | 0.2 | 1.9 |
| Jun | 0.1 | 2.1 | 0.1 | 1.9 |
| May | 0.2 | 2.1 | 0.2 | 2.0 |
| Apr | 0.2 | 2.0 | 0.2 | 1.8 |
| AE ∆% Apr-Jul | 1.8 | 2.1 | ||
| Mar | 0.2 | 1.5 | 0.2 | 1.7 |
| Feb | 0.1 | 1.1 | 0.1 | 1.6 |
| Jan | 0.3 | 1.6 | 0.1 | 1.6 |
| Dec 2013 | 0.3 | 1.5 | 0.2 | 1.7 |
| AE ∆% Dec-Mar | 2.7 | 1.8 | ||
| Nov | 0.2 | 1.2 | 0.2 | 1.7 |
| Oct | 0.1 | 1.0 | 0.1 | 1.7 |
| AE ∆% Oct-Nov | 1.8 | 1.8 | ||
| Sep | 0.0 | 1.2 | 0.2 | 1.7 |
| Aug | 0.2 | 1.5 | 0.2 | 1.8 |
| Jul | 0.2 | 2.0 | 0.2 | 1.7 |
| Jun | 0.2 | 1.8 | 0.2 | 1.6 |
| May | 0.0 | 1.4 | 0.1 | 1.7 |
| AE ∆% May-Sep | 1.4 | 2.2 | ||
| Apr | -0.2 | 1.1 | 0.0 | 1.7 |
| Mar | -0.3 | 1.5 | 0.1 | 1.9 |
| AE ∆% Mar-Apr | -3.0 | 0.6 | ||
| Feb | 0.5 | 2.0 | 0.1 | 2.0 |
| AE ∆% Feb | 6.2 | 1.2 | ||
| Jan | 0.2 | 1.6 | 0.2 | 1.9 |
| Dec 2012 | 0.0 | 1.7 | 0.2 | 1.9 |
| Nov | -0.2 | 1.8 | 0.1 | 1.9 |
| AE ∆% Nov-Jan | 0.0 | 2.0 | ||
| Oct | 0.3 | 2.2 | 0.2 | 2.0 |
| Sep | 0.5 | 2.0 | 0.2 | 2.0 |
| Aug | 0.6 | 1.7 | 0.1 | 1.9 |
| AE ∆% Aug-Oct | 5.7 | 2.0 | ||
| Jul | 0.0 | 1.4 | 0.2 | 2.1 |
| Jun | -0.1 | 1.7 | 0.2 | 2.2 |
| May | -0.2 | 1.7 | 0.1 | 2.3 |
| AE ∆% May-Jul | -1.2 | 2.0 | ||
| Apr | 0.2 | 2.3 | 0.2 | 2.3 |
| Mar | 0.2 | 2.7 | 0.2 | 2.3 |
| Feb | 0.2 | 2.9 | 0.1 | 2.2 |
| AE ∆% Feb-Apr | 2.4 | 2.0 | ||
| Jan | 0.3 | 2.9 | 0.2 | 2.3 |
| Dec 2011 | 0.0 | 3.0 | 0.2 | 2.2 |
| AE ∆% Dec-Jan | 1.8 | 2.4 | ||
| Nov | 0.2 | 3.4 | 0.2 | 2.2 |
| Oct | 0.1 | 3.5 | 0.2 | 2.1 |
| AE ∆% Oct-Nov | 1.8 | 2.4 | ||
| Sep | 0.2 | 3.9 | 0.1 | 2.0 |
| Aug | 0.3 | 3.8 | 0.3 | 2.0 |
| Jul | 0.3 | 3.6 | 0.2 | 1.8 |
| AE ∆% Jul-Sep | 3.2 | 2.4 | ||
| Jun | 0.0 | 3.6 | 0.2 | 1.6 |
| May | 0.3 | 3.6 | 0.2 | 1.5 |
| AE ∆% May-Jun | 1.8 | 2.4 | ||
| Apr | 0.5 | 3.2 | 0.1 | 1.3 |
| Mar | 0.5 | 2.7 | 0.1 | 1.2 |
| Feb | 0.3 | 2.1 | 0.2 | 1.1 |
| Jan | 0.3 | 1.6 | 0.2 | 1.0 |
| AE ∆% Jan-Apr | 4.9 | 1.8 | ||
| Dec 2010 | 0.4 | 1.5 | 0.1 | 0.8 |
| Nov | 0.3 | 1.1 | 0.1 | 0.8 |
| Oct | 0.3 | 1.2 | 0.1 | 0.6 |
| Sep | 0.2 | 1.1 | 0.1 | 0.8 |
| Aug | 0.1 | 1.1 | 0.1 | 0.9 |
| Jul | 0.2 | 1.2 | 0.1 | 0.9 |
| Jun | 0.0 | 1.1 | 0.1 | 0.9 |
| May | -0.1 | 2.0 | 0.1 | 0.9 |
| Apr | 0.0 | 2.2 | 0.0 | 0.9 |
| Mar | 0.0 | 2.3 | 0.0 | 1.1 |
| Feb | -0.1 | 2.1 | 0.0 | 1.3 |
| Jan | 0.1 | 2.6 | -0.1 | 1.6 |
Note: Core: excluding food and energy; AE: annual equivalent
Source: US Bureau of Labor Statistics http://www.bls.gov/cpi/
The behavior of the US consumer price index NSA from 2001 to 2018 is in Chart I-20. Inflation in the US is very dynamic without deflation risks that would justify symmetric inflation targets. The hump in 2008 originated in the carry trade from interest rates dropping to zero into commodity futures. There is no other explanation for the increase of the Cushing OK Crude Oil Future Contract 1 from $55.64/barrel on Jan 9, 2007 to $145.29/barrel on July 3, 2008 during deep global recession, collapsing under a panic of flight into government obligations and the US dollar to $37.51/barrel on Feb 13, 2009 and then rising by carry trades to $113.93/barrel on Apr 29, 2012, collapsing again and then recovering again to $105.23/barrel, all during mediocre economic recovery with peaks and troughs influenced by bouts of risk appetite and risk aversion (data from the US Energy Information Administration EIA, http://www.eia.gov/). The unwinding of the carry trade with the TARP announcement of toxic assets in banks channeled cheap money into government obligations (see Cochrane and Zingales 2009).
Chart I-20, US, Consumer Price Index, NSA, 2001-2018
Source: US Bureau of Labor Statistics http://www.bls.gov/cpi/
Chart I-21 provides 12-month percentage changes of the consumer price index from 2001 to 2018. There was no deflation or threat of deflation from 2008 into 2009. Commodity prices collapsed during the panic of toxic assets in banks. When stress tests in 2009 revealed US bank balance sheets in much stronger position, cheap money at zero opportunity cost exited government obligations and flowed into carry trades of risk financial assets. Increases in commodity prices drove again the all items CPI with interruptions during risk aversion originating in multiple fears but especially from the sovereign debt crisis of Europe.
Chart I-21, US, Consumer Price Index, 12-Month Percentage Change, NSA, 2001-2018
Source: US Bureau of Labor Statistics http://www.bls.gov/cpi/
The trend of increase of the consumer price index excluding food and energy in Chart I-22 does not reveal any threat of deflation that would justify symmetric inflation targets. There are mild oscillations in a neat upward trend.
Chart I-22, US, Consumer Price Index Excluding Food and Energy, NSA, 2001-2018
Source: US Bureau of Labor Statistics http://www.bls.gov/cpi/
Chart I-23 provides 12-month percentage change of the consumer price index excluding food and energy. Past-year rates of inflation fell toward 1 percent from 2001 into 2003 because of the recession and the decline of commodity prices beginning before the recession with declines of real oil prices. Near zero interest rates with fed funds at 1 percent between Jun 2003 and Jun 2004 stimulated carry trades of all types, including in buying homes with subprime mortgages in expectation that low interest rates forever would increase home prices permanently, creating the equity that would permit the conversion of subprime mortgages into creditworthy mortgages (Gorton 2009EFM; see http://cmpassocregulationblog.blogspot.com/2011/07/causes-of-2007-creditdollar-crisis.html). Inflation rose and then collapsed during the unwinding of carry trades and the housing debacle of the global recession. Carry trades into 2011 and 2012 gave a new impulse to CPI inflation, all items and core. Symmetric inflation targets destabilize the economy by encouraging hunts for yields that inflate and deflate financial assets, obscuring risk/return decisions on production, investment, consumption and hiring.
Chart I-23, US, Consumer Price Index Excluding Food and Energy, 12-Month Percentage Change, NSA, 2001-2018
Source: US Bureau of Labor Statistics
Headline and core producer price indexes are in Table I-6. The headline PPI SA increased 1.0 percent in May 2018 and increased 4.1 percent NSA in the 12 months ending in May 2018. The core PPI SA increased 0.2 percent in May 2018 and increased 2.2 percent in 12 months. Analysis of annual equivalent rates of change shows inflation waves similar to those worldwide. In the first wave, the absence of risk aversion from the sovereign risk crisis in Europe motivated the carry trade from zero interest rates into commodity futures that caused the annual equivalent rate of 11.1 percent in the headline PPI in Jan-Apr 2011 and 3.7 percent in the core PPI. In the second wave, commodity futures prices collapsed in Jun 2011 with the return of risk aversion originating in the sovereign risk crisis of Europe. The annual equivalent rate of headline PPI inflation collapsed to 0.6 percent in May-Jun 2011 but the core annual equivalent inflation rate was higher at 2.4 percent. In the third wave, headline PPI inflation resuscitated with annual equivalent at 4.1 percent in Jul-Sep 2011 and core PPI inflation at 3.2 percent. Core PPI inflation was persistent throughout 2011, jumping from annual equivalent at 2.0 percent in the first three months of 2010 to 3.0 percent in 12 months ending in Dec 2011. Unconventional monetary policy is based on the proposition that core rates reflect more fundamental inflation and are thus better predictors of the future. In practice, the relation of core and headline inflation is as difficult to predict as future inflation (see IIID Supply Shocks in http://cmpassocregulationblog.blogspot.com/2011/05/slowing-growth-global-inflation-great.html). In the fourth wave, risk aversion originating in the lack of resolution of the European debt crisis caused unwinding of carry trades with annual equivalent headline PPI inflation of 0.0 percent in Oct-Dec 2011 and 2.0 percent in the core annual equivalent. In the fifth wave from Jan to Mar 2012, annual equivalent inflation was 3.2 percent for the headline index but 3.2 percent for the core index excluding food and energy. In the sixth wave, annual equivalent inflation in Apr-May 2012 during renewed risk aversion was minus 4.1 percent for the headline PPI and 1.8 percent for the core. In the seventh wave, continuing risk aversion caused reversal of carry trades into commodity exposures with annual equivalent headline inflation of minus 1.2 percent in Jun-Jul 2012 while core PPI inflation was at annual equivalent 3.7 percent. In the eighth wave, relaxed risk aversion because of the announcement of the impaired bond buying program or Outright Monetary Transactions (OMT) of the European Central Bank (http://www.ecb.int/press/pr/date/2012/html/pr120906_1.en.html) induced carry trades that drove annual equivalent inflation of producer prices of the United States at 13.4 percent in Aug-Sep 2012 and 1.2 percent in the core index. In the ninth wave, renewed risk aversion caused annual equivalent inflation of minus 2.4 percent in Oct 2012-Dec 2012 in the headline index and 1.2 percent in the core index. In the tenth wave, annual equivalent inflation was 7.4 percent in the headline index in Jan-Feb 2013 and 1.8 percent in the core index. In the eleventh wave, annual equivalent inflation was minus 7.0 percent in Mar-Apr 2012 and 1.2 percent for the core index. In the twelfth wave, annual equivalent inflation returned at 2.7 percent in May-Aug 2013 and 1.2 percent in the core index. In the thirteenth wave, portfolio reallocations away from commodities and into equities reversed commodity carry trade with annual equivalent inflation of 0.8 percent in Sep-Nov 2013 in the headline PPI and 1.6 percent in the core. In the fourteenth wave, annual equivalent inflation returned at 5.3 percent annual equivalent for the headline index in Dec 2013-Feb 2014 and 4.1 percent for the core index. In the fifteenth wave, annual equivalent inflation was 3.7 percent for the general PPI index in Mar 2014 and 0.0 percent for the core PPI index. In the sixteenth wave, annual equivalent headline PPI inflation increased at 1.5 percent in Apr-Jul 2014 and 1.8 percent for the core PPI. In the seventeenth wave, annual equivalent inflation in Aug-Nov 2014 was minus 3.0 percent and 1.8 percent for the core index. In the eighteenth wave, annual equivalent inflation fell at 17.6 percent for the general index in Dec 2014 to Jan 2015 and increased at 3.0 percent in the core index. In the nineteenth wave, annual equivalent inflation increased at 1.2 percent in Feb 2015 and increased at 3.7 percent for the core index. In the twentieth wave, annual equivalent producer prices increased at 3.7 percent in Mar 2015 and the core at 2.4 percent. In the twenty-first wave, producer prices fell at 7.0 percent annual equivalent in Apr 2015 while the core index increased at 1.2 percent. In the twenty-second wave, producer prices increased at annual equivalent 12.0 percent in May-Jun 2015 and core producer prices at 2.4 percent. In the twenty-third wave, producer prices fell at 2.4 percent in Jul 2015 and the core index increased at 2.4 percent. In the twenty-fourth wave, annual equivalent inflation fell at 7.4 percent in Aug-Oct 2015 and the core index changed at 0.0 percent annual equivalent. In the twenty-fifth wave, annual equivalent inflation was 2.4 percent in Nov 2015 with the core at 1.2 percent. In the twenty-sixth wave, the headline PPI fell at annual equivalent 7.0 percent and the core increased at 2.0 percent in Dec 2015-Feb 2016. In the twenty-seventh wave, annual equivalent inflation was 4.5 percent for the central index in Mar-May 2016 and 1.6 percent for the core. In the twenty-eighth wave, annual equivalent inflation was 8.7 percent for the headline index in Jun 2016 and 3.7 percent for the core. In the twenty-ninth wave, producer prices fell at annual equivalent 1.2 percent in Jul 2016 and core producer prices changed at 0.0 percent. In the thirtieth wave, producer prices fell at 3.5 percent annual equivalent in Aug 2016 while core producer prices increased at 2.4 percent. In the thirty-first wave, producer prices increased at annual equivalent 5.5 percent in Sep-Oct 2016 while core prices increased at 1.2 percent. In the thirty-second wave, producer prices decreased at 3.5 percent annual equivalent in Nov 2016 and the core index increased at 1.2 percent. In the thirty-third wave, producer prices increased at 10.0 percent in Dec 2016 and the core index increased at 3.7 percent. In the thirty-fourth wave, producer prices increased at 11.4 percent in Jan 2017 while the core increased at 2.4 percent. In the thirty-fifth wave, producer prices increased at 1.2 percent in Feb 2017 while the core index increased at 1.2 percent. In the thirty-sixth wave, producer prices increased at annual equivalent 1.2 percent in Mar 2017 while core producer prices increased at 3.7 percent. In the thirty-seventh wave, annual equivalent inflation of the headline index was at 7.4 percent in Apr 2017 and 4.9 percent for the core. In the thirty-eighth wave, producer prices fell at 7.0 percent annual equivalent in May 2017 while core producer prices changed at 0.0 percent. In the thirty-ninth wave, producer prices increased at annual equivalent 1.2 percent in Jun 2017 while core producer prices increased at 2.4 percent. In the fortieth wave, headline producer prices fell at 1.2 percent annual equivalent in Jul 2017 while core prices increased at 1.2 percent. In the forty-first wave, central producer prices increased at 7.4 percent annual equivalent in Aug-Sep 2017 while core prices increased at 1.8 percent. In the forty-second wave, producer prices increased at annual equivalent 7.4 percent in Oct-Nov 2017 while core producer prices increased at 4.3 percent. In the forty-third wave, producer prices decreased at annual equivalent 1.2 percent in Dec 2017 while core prices increased at 1.2 percent. In the forty-fourth wave, producer prices increased at 7.4 percent annual equivalent in Jan 2018 while core producer prices changed at 0.0 percent. In the forty-fifth wave, producer prices fell at annual equivalent 1.2 percent in Feb 2018 while core prices increased at 1.2 percent. In the forty-sixth wave, producer prices increased at 2.4 percent annual equivalent in Mar 2018 while core prices increased at 2.4 percent. In the forty-seventh wave, producer prices fell at 1.2 percent annual equivalent in Apr 2018 while core prices increased at 3.7 percent. In the forty-eighth wave, producer prices increased at annual equivalent 12.7 percent in May 2018 while core prices increased at 2.4 percent. It is almost impossible to forecast PPI inflation and its relation to CPI inflation. “Inflation surprise” by monetary policy could be proposed to climb along a downward sloping Phillips curve, resulting in higher inflation but lower unemployment (see Kydland and Prescott 1977, Barro and Gordon 1983 and past comments of this blog 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 http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html). The architects of monetary policy would require superior inflation forecasting ability compared to forecasting naivety by everybody else. In practice, we are all naïve in forecasting inflation and other economic variables and events.
Table I-6, US, Headline and Core PPI Inflation Monthly SA and 12-Month NSA ∆%
| Finished | Finished | Finished Core SA | Finished Core NSA | |
| May 2018 | 1.0 | 4.1 | 0.2 | 2.2 |
| AE May | 12.7 | 2.4 | ||
| Apr | -0.1 | 2.4 | 0.3 | 1.9 |
| AE Apr | -1.2 | 3.7 | ||
| Mar | 0.2 | 3.0 | 0.2 | 2.0 |
| AE Mar | 2.4 | 2.4 | ||
| Feb | -0.1 | 2.7 | 0.1 | 1.9 |
| AE Feb | -1.2 | 1.2 | ||
| Jan | 0.6 | 2.9 | 0.0 | 1.8 |
| AE Jan | 7.4 | 0.0 | ||
| Dec 2017 | -0.1 | 3.2 | 0.1 | 2.0 |
| AE Dec | -1.2 | 1.2 | ||
| Nov | 1.0 | 4.2 | 0.3 | 2.1 |
| Oct | 0.2 | 2.9 | 0.4 | 2.0 |
| AE Oct-Nov | 7.4 | 4.3 | ||
| Sep | 0.6 | 3.3 | 0.1 | 1.7 |
| Aug | 0.6 | 3.0 | 0.2 | 1.8 |
| AE Aug-Sep | 7.4 | 1.8 | ||
| Jul | -0.1 | 2.1 | 0.1 | 1.8 |
| AE Jul | -1.2 | 1.2 | ||
| Jun | 0.1 | 2.1 | 0.2 | 1.7 |
| AE Jun | 1.2 | 2.4 | ||
| May | -0.6 | 2.8 | 0.0 | 1.9 |
| AE May | -7.0 | 0.0 | ||
| Apr | 0.6 | 4.0 | 0.4 | 2.0 |
| AE Apr | 7.4 | 4.9 | ||
| Mar | 0.1 | 3.8 | 0.3 | 1.8 |
| AE Mar | 1.2 | 3.7 | ||
| Feb | 0.1 | 3.8 | 0.1 | 1.6 |
| AE Feb | 1.2 | 1.2 | ||
| Jan | 0.9 | 2.9 | 0.2 | 1.7 |
| AE Jan | 11.4 | 2.4 | ||
| Dec 2016 | 0.8 | 1.9 | 0.3 | 1.7 |
| AE Dec | 10.0 | 3.7 | ||
| Nov | -0.3 | 0.4 | 0.1 | 1.6 |
| AE Nov | -3.5 | 1.2 | ||
| Oct | 0.5 | 0.7 | 0.1 | 1.6 |
| Sep | 0.4 | -0.1 | 0.1 | 1.4 |
| AE Sep-Oct | 5.5 | 1.2 | ||
| Aug | -0.3 | -1.9 | 0.2 | 1.4 |
| AE Aug | -3.5 | 2.4 | ||
| Jul | -0.1 | -2.0 | 0.0 | 1.2 |
| AE Jul | -1.2 | 0.0 | ||
| Jun | 0.7 | -2.0 | 0.3 | 1.5 |
| AE Jun | 8.7 | 3.7 | ||
| May | 0.6 | -2.2 | 0.1 | 1.6 |
| Apr | 0.3 | -1.5 | 0.2 | 1.6 |
| Mar | 0.2 | -2.3 | 0.1 | 1.5 |
| AE Mar-May | 4.5 | 1.6 | ||
| Feb | -0.8 | -2.0 | 0.1 | 1.5 |
| Jan | -0.3 | -1.2 | 0.2 | 1.7 |
| Dec 2015 | -0.7 | -2.7 | 0.2 | 1.8 |
| AE Dec-Feb | -7.0 | 2.0 | ||
| Nov | 0.2 | -3.3 | 0.1 | 1.7 |
| AE Nov | 2.4 | 1.2 | ||
| Oct | -0.3 | -4.0 | -0.1 | 1.8 |
| Sep | -1.3 | -4.1 | 0.1 | 2.1 |
| Aug | -0.3 | -3.1 | 0.0 | 2.1 |
| AE ∆% Aug-Oct | -7.4 | 0.0 | ||
| Jul | -0.2 | -2.8 | 0.2 | 2.3 |
| AE ∆% Jul | -2.4 | 2.4 | ||
| Jun | 0.6 | -2.6 | 0.5 | 2.3 |
| May | 1.3 | -2.9 | 0.1 | 2.0 |
| AE ∆% May-Jun | 12.0 | 2.4 | ||
| Apr | -0.6 | -4.5 | 0.1 | 2.0 |
| AE ∆% Apr | -7.0 | 1.2 | ||
| Mar | 0.3 | -3.3 | 0.2 | 2.1 |
| AE ∆% Mar | 3.7 | 2.4 | ||
| Feb | 0.1 | -3.2 | 0.3 | 1.9 |
| AE ∆% Feb | 1.2 | 3.7 | ||
| Jan | -1.8 | -3.0 | 0.4 | 1.7 |
| Dec 2014 | -1.4 | -0.6 | 0.1 | 1.7 |
| AE ∆% Dec-Jan | -17.6 | 3.0 | ||
| Nov | -0.4 | 1.1 | 0.0 | 2.0 |
| Oct | -0.3 | 1.8 | 0.3 | 2.2 |
| Sep | -0.3 | 2.2 | 0.1 | 2.1 |
| Aug | 0.0 | 2.3 | 0.2 | 1.9 |
| AE ∆% Aug-Nov | -3.0 | 1.8 | ||
| July | 0.0 | 2.9 | 0.1 | 1.9 |
| Jun | 0.2 | 2.8 | 0.2 | 1.9 |
| May | -0.2 | 2.5 | 0.2 | 1.8 |
| Apr | 0.5 | 3.1 | 0.1 | 1.7 |
| AE ∆% Apr-Jul | 1.5 | 1.8 | ||
| Mar | 0.3 | 1.8 | 0.0 | 1.7 |
| AE ∆% Mar | 3.7 | 0.0 | ||
| Feb | 0.1 | 1.3 | 0.1 | 1.9 |
| Jan | 0.8 | 1.6 | 0.5 | 2.0 |
| Dec 2013 | 0.4 | 1.4 | 0.4 | 1.6 |
| AE ∆% Dec-Feb | 5.3 | 4.1 | ||
| Nov | 0.3 | 0.8 | 0.2 | 1.3 |
| Oct | 0.2 | 0.3 | 0.1 | 1.2 |
| Sep | -0.3 | 0.2 | 0.1 | 1.2 |
| AE ∆% Sep-Nov | 0.8 | 1.6 | ||
| Aug | 0.5 | 1.2 | 0.1 | 1.2 |
| Jul | -0.1 | 2.1 | 0.1 | 1.3 |
| Jun | 0.1 | 2.3 | 0.1 | 1.6 |
| May | 0.4 | 1.6 | 0.1 | 1.7 |
| AE ∆% May-Aug | 2.7 | 1.2 | ||
| Apr | -0.6 | 0.5 | 0.1 | 1.7 |
| Mar | -0.6 | 1.1 | 0.1 | 1.7 |
| AE ∆% Mar-Apr | -7.0 | 1.2 | ||
| Feb | 0.6 | 1.8 | 0.2 | 1.8 |
| Jan | 0.6 | 1.5 | 0.1 | 1.8 |
| AE ∆% Jan-Feb | 7.4 | 1.8 | ||
| Dec 2012 | -0.2 | 1.4 | 0.0 | 2.1 |
| Nov | -0.5 | 1.4 | 0.2 | 2.2 |
| Oct | 0.1 | 2.3 | 0.1 | 2.2 |
| AE ∆% Oct-Dec | -2.4 | 1.2 | ||
| Sep | 0.9 | 2.1 | 0.0 | 2.4 |
| Aug | 1.2 | 1.9 | 0.2 | 2.6 |
| AE ∆% Aug-Sep | 13.4 | 1.2 | ||
| Jul | 0.2 | 0.5 | 0.4 | 2.6 |
| Jun | -0.4 | 0.7 | 0.2 | 2.6 |
| AE ∆% Jun-Jul | -1.2 | 3.7 | ||
| May | -0.6 | 0.6 | 0.1 | 2.7 |
| Apr | -0.1 | 1.8 | 0.2 | 2.7 |
| AE ∆% Apr-May | -4.1 | 1.8 | ||
| Mar | 0.1 | 2.7 | 0.2 | 2.9 |
| Feb | 0.3 | 3.4 | 0.2 | 3.1 |
| Jan | 0.4 | 4.1 | 0.4 | 3.1 |
| AE ∆% Jan-Mar | 3.2 | 3.2 | ||
| Dec 2011 | -0.1 | 4.7 | 0.2 | 3.0 |
| Nov | 0.3 | 5.7 | 0.1 | 3.0 |
| Oct | -0.2 | 5.9 | 0.2 | 2.9 |
| AE ∆% Oct-Dec | 0.0 | 2.0 | ||
| Sep | 0.9 | 7.1 | 0.3 | 2.8 |
| Aug | -0.3 | 6.6 | 0.2 | 2.7 |
| Jul | 0.4 | 7.2 | 0.3 | 2.7 |
| AE ∆% Jul-Sep | 4.1 | 3.2 | ||
| Jun | -0.4 | 7.0 | 0.3 | 2.3 |
| May | 0.5 | 7.1 | 0.1 | 2.1 |
| AE ∆% May-Jun | 0.6 | 2.4 | ||
| Apr | 0.9 | 6.7 | 0.3 | 2.3 |
| Mar | 0.7 | 5.7 | 0.3 | 2.0 |
| Feb | 1.1 | 5.5 | 0.2 | 1.8 |
| Jan | 0.8 | 3.7 | 0.4 | 1.6 |
| AE ∆% Jan-Apr | 11.1 | 3.7 | ||
| Dec 2010 | 0.9 | 3.8 | 0.2 | 1.4 |
| Nov | 0.4 | 3.4 | 0.0 | 1.2 |
| Oct | 0.8 | 4.3 | 0.0 | 1.6 |
| Sep | 0.3 | 3.9 | 0.2 | 1.6 |
| Aug | 0.6 | 3.3 | 0.1 | 1.3 |
| Jul | 0.1 | 4.1 | 0.1 | 1.5 |
| Jun | -0.3 | 2.7 | 0.1 | 1.1 |
| May | 0.0 | 5.1 | 0.3 | 1.3 |
| Apr | 0.0 | 5.4 | 0.0 | 0.9 |
| Mar | 0.7 | 5.9 | 0.2 | 0.9 |
| Feb | -0.7 | 4.1 | 0.1 | 1.0 |
| Jan | 1.0 | 4.5 | 0.2 | 1.0 |
Note: Core: excluding food and energy; AE: annual equivalent
Source: US Bureau of Labor Statistics http://www.bls.gov/ppi/data.htm
The US producer price index NSA from 2000 to 2018 is in Chart I-24. There are two episodes of decline of the PPI during recessions in 2001 and in 2008. Barsky and Kilian (2004) consider the 2001 episode as one in which real oil prices were declining when recession began. Recession and the fall of commodity prices instead of generalized deflation explain the behavior of US inflation in 2008. There is similar collapse of producer prices into 2015 as in 2009 caused by the drop of
commodity prices.
Chart I-24, US, Producer Price Index, NSA, 2000-2018
Source: US Bureau of Labor Statistics
Twelve-month percentage changes of the PPI NSA from 2000 to 2018 are in Chart I-25. It may be possible to forecast trends a few months in the future under adaptive expectations but turning points are almost impossible to anticipate especially when related to fluctuations of commodity prices in response to risk aversion. In a sense, monetary policy has been tied to behavior of the PPI in the negative 12-month rates in 2001 to 2003 and then again in 2009 to 2010. There is similar sharp decline of inflation into 2015 caused by the drop of commodities. Monetary policy following deflation fears caused by commodity price fluctuations would introduce significant volatility and risks in financial markets and eventually in consumption and investment.
Chart I-25, US, Producer Price Index, 12-Month Percentage Change NSA, 2000-2018
Source: US Bureau of Labor Statistics
The US PPI excluding food and energy from 2000 to 2018 is in Chart I-26. There is here again a smooth trend of inflation instead of prolonged deflation as in Japan.
Chart I-26, US, Producer Price Index Excluding Food and Energy, NSA, 2000-2018
Source: US Bureau of Labor Statistics
Twelve-month percentage changes of the producer price index excluding food and energy are in Chart I-27. Fluctuations replicate those in the headline PPI. There is an evident trend of increase of 12-month rates of core PPI inflation in 2011 but lower rates in 2012-2014. Prices rose less rapidly into 2015-2018 as during earlier fluctuations.
Chart I-27, US, Producer Price Index Excluding Food and Energy, NSA, 12-Month Percentage Changes, 2000-2018
Source: US Bureau of Labor Statistics
The US producer price index of energy goods from 2000 to 2018 is in Chart I-28. There is a clear upward trend with fluctuations, which would not occur under persistent deflation.
Chart I-28, US, Producer Price Index Finished Energy Goods, NSA, 2000-2018
Source: US Bureau of Labor Statistics
Chart I-29 provides 12-month percentage changes of the producer price index of energy goods from 2000 to 2018. Barsky and Killian (2004) relate the episode of declining prices of energy goods in 2001 to 2002 to the analysis of decline of real oil prices. Interest rates dropping to zero during the global recession in 2008 induced carry trades that explain the rise of the PPI of energy goods toward 30 percent. Bouts of risk aversion with policy interest rates held close to zero explain the fluctuations in the 12-month rates of the PPI of energy goods in the expansion phase of the economy. Symmetric inflation targets induce significant instability in inflation and interest rates with adverse effects on financial markets and the overall economy.
Chart I-29, US, Producer Price Index Energy Goods, 12-Month Percentage Change, NSA, 2000-2018
Source: US Bureau of Labor Statistics
Effective with the January 2014 Producer Price Index (PPI) data release in February 2014 (https://www.bls.gov/news.release/archives/ppi_02192014.pdf 8), “BLS transitions from the Stage of Processing (SOP) to the Final Demand-Intermediate Demand (FD-ID) aggregation system. This shift results in significant changes to the PPI news release, as well as other documents available from PPI. The transition to the FD-ID system is the culmination of a long-standing PPI objective to improve the current SOP aggregation system by incorporating PPIs for services, construction, government purchases, and exports. In comparison to the SOP system, the FD-ID system more than doubles PPI coverage of the United States economy to over 75 percent of in-scope domestic production. The FD-ID system was introduced as a set of experimental indexes in January 2011. Nearly all new FD-ID goods, services, and construction indexes provide historical data back to either November 2009 or April 2010, while the indexes for goods that correspond with the historical SOP indexes go back to the 1970s or earlier.”
Headline and core final demand producer price indexes are in Table I-6B. The headline FD PPI SA increased 0.5 percent in May 2018 and increased 3.1 percent NSA in the 12 months ending in May 2018. The core FD PPI SA increased 0.3 percent in May 2018 and increased 2.4 percent in 12 months. Analysis of annual equivalent rates of change shows inflation waves similar to those worldwide. In the first wave, the absence of risk aversion from the sovereign risk crisis in Europe motivated the carry trade from zero interest rates into commodity futures that caused the average equivalent rate of 7.4 percent in the headline FD PPI in Jan-Apr 2011 and 4.6 percent in the core FD PPI. In the second wave, commodity futures prices collapsed in Jun 2011 with the return of risk aversion originating in the sovereign risk crisis of Europe. The annual equivalent rate of headline FD PPI inflation collapsed to 2.4 percent in May-Jun 2011 but the core annual equivalent inflation rate was at 2.4 percent. In the third wave, headline FD PPI inflation resuscitated with annual equivalent at 3.2 percent in Jul-Sep 2011 and core PPI inflation at 3.2 percent. Core FD PPI inflation was persistent throughout 2011, from annual equivalent at 4.6 percent in the first four months of 2011 to 2.6 percent in 12 months ending in Dec 2011. Unconventional monetary policy is based on the proposition that core rates reflect more fundamental inflation and are thus better predictors of the future. In practice, the relation of core and headline inflation is as difficult to predict as future inflation (see IIID Supply Shocks in http://cmpassocregulationblog.blogspot.com/2011/05/slowing-growth-global-inflation-great.html). In the fourth wave, risk aversion originating in the lack of resolution of the European debt crisis caused unwinding of carry trades with annual equivalent headline FD PPI inflation of minus 0.8 percent in Oct-Dec 2011 and minus 0.4 percent in the core annual equivalent. In the fifth wave from Jan to Mar 2012, annual equivalent inflation was 3.7 percent for the headline index and 3.7 percent for the core index excluding food and energy. In the sixth wave, annual equivalent inflation in Apr-May 2012 during renewed risk aversion was 1.2 percent for the headline FD PPI and 3.0 percent for the core. In the seventh wave, continuing risk aversion caused reversal of carry trades into commodity exposures with annual equivalent headline inflation of minus 2.4 percent in Jun-Jul 2012 while core FD PPI inflation was at annual equivalent minus 1.2 percent. In the eighth wave, relaxed risk aversion because of the announcement of the impaired bond buying program or Outright Monetary Transactions (OMT) of the European Central Bank (http://www.ecb.int/press/pr/date/2012/html/pr120906_1.en.html) induced carry trades that drove annual equivalent inflation of final demand producer prices of the United States at 6.2 percent in Aug-Sep 2012 and 1.2 percent in the core index. In the ninth wave, renewed risk aversion caused annual equivalent inflation of 0.8 percent in Oct 2011-Dec 2012 in the headline index and 2.8 percent in the core index. In the tenth wave, annual equivalent inflation was 3.0 percent in the headline index in Jan-Feb 2013 and 0.6 percent in the core index. In the eleventh wave, annual equivalent price change was minus 1.2 percent in Mar-Apr 2013 and 2.4 percent for the core index. In the twelfth wave, annual equivalent inflation returned at 1.8 percent in May-Aug 2013 and 1.6 percent in the core index. In the thirteenth wave, portfolio reallocations away from commodities and into equities reversed commodity carry trade with annual equivalent inflation of 1.6 percent in Sep-Nov 2013 in the headline FD PPI and 2.0 percent in the core. In the fourteenth wave, annual equivalent inflation was 2.4 percent annual equivalent for the headline index in Dec 2013-Feb 2014 and 1.6 percent for the core index. In the fifteenth wave, annual equivalent inflation increased to 2.4 percent in the headline FD PPI and 2.7 percent in the core in Mar-Jul 2014. In the sixteenth wave, annual equivalent inflation was minus 1.2 percent for the headline FD index and minus 0.6 percent for the core FD index in Aug-Sep 2014. In the seventeenth wave, annual equivalent inflation was 2.4 percent for the headline FD and 4.9 percent for the core FD in Oct 2014. In the eighteenth wave, annual equivalent inflation was minus 3.0 percent for the headline FDI and 1.2 percent for the core in Nov-Dec 2014. In the nineteenth wave, annual equivalent inflation was minus 6.4 percent for the general index and minus 2.4 percent for the core in Jan-Feb 2015. In the twentieth wave, annual equivalent inflation was 1.2 percent for the general index in Mar 2015 and 0.0 percent for the core. In the twenty-first wave, final demand prices decreased at annual equivalent 1.2 percent for the headline index in Apr 2015 and increased at 2.4 percent for the core index. In the twenty-second wave, annual equivalent inflation returned at 3.7 percent for the headline index in May-Jul 2015 and at 2.0 percent for the core index. In the twenty-third wave, the headline final demand index fell at 2.4 percent annual equivalent in Aug 2015 and the core changed at 0.0 percent annual equivalent. In the twenty-fourth wave, FD prices fell at annual equivalent 4.1 percent in Sep-Oct 2015. In the twenty-fifth wave, FD prices increased at 1.2 percent annual equivalent in Nov 2015. In the twenty-sixth wave, FD prices decreased at 2.4 percent annual equivalent in Dec 2015. In the twenty-seventh wave, FD prices increased at 6.2 percent annual equivalent in Jan 2016 and the core FD increased at 6.2 percent. In the twenty-eighth wave, FD prices fell at annual equivalent 2.4 percent in Feb-Mar 2016 while the core decreased at 0.6 percent. In the twenty-ninth wave, FD prices increased at 4.1 percent annual equivalent in Apr-Jun 2016 and core FD increased at 2.4 percent. In the thirtieth wave, final demand prices changed at 0.0 percent in annual equivalent in Jul 2016 while the core changed at 0.0 percent. In the thirty-first wave, final demand prices decreased at annual equivalent 3.5 percent in Aug 2016 and the core decreased at 1.2 percent. In the thirty-second wave, final demand prices increased at annual equivalent 3.7 percent in Sep 2016 while core final demand increased at 2.4 percent. In the thirty-third wave, final demand prices increased at 3.7 percent and core final demand prices increased at 2.4 percent in Oct 2016. In the thirty-fourth wave, final demand producer prices increased at 3.0 percent annual equivalent in Nov-Dec 2016 while the core increased at 1.8 percent. In the thirty-fifth wave, final demand producer prices increased at 6.2 percent in Jan 2017 while core prices increased at 4.9 percent. In the thirty-sixth wave, final demand prices decreased at 1.2 percent annual equivalent in Feb 2017 while the core index decreased at 1.2 percent. In the thirty-seventh wave, final demand prices increased at 1.2 percent annual equivalent in Mar 2017 while the core index increased at 2.4 percent. In the thirty-eighth wave, final demand prices increased at 4.9 percent in Apr 2017 while the core increased at 4.9 percent. In the thirty-ninth wave, final demand prices increased at annual equivalent 1.2 percent in May-Jun 2017 while core prices increased at 1.8 percent. In the fortieth wave, final demand prices increased at 1.2 percent annual equivalent in Jul 2017 while core prices increased at 2.4 percent. In the forty-first wave, final demand prices increased at 4.3 percent annual equivalent in Aug-Nov 2017 while core prices increased at 2.7 percent. In the forty-second wave, final demand prices changed at annual equivalent 0.0 percent in Dec 2017 while core prices decreased at 1.2 percent. In the forty-third wave, final demand prices increased at annual equivalent 4.1 percent in Jan-Mar 2018 while core prices increased at 4.1 percent. In the forty-fourth wave, final demand increased at 3.7 percent in Apr-May 2018 while core prices increased at 3.0 percent. It is almost impossible to forecast PPI inflation and its relation to CPI inflation. “Inflation surprise” by monetary policy could be proposed to climb along a downward sloping Phillips curve, resulting in higher inflation but lower unemployment (see Kydland and Prescott 1977, Barro and Gordon 1983 and past comments of this blog 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 http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html). The architects of monetary policy would require superior inflation forecasting ability compared to forecasting naivety by everybody else. In practice, we are all naïve in forecasting inflation and other economic variables and events.
Table I-6B, US, Headline and Core Final Demand Producer Price Inflation Monthly SA and 12-Month NSA ∆%
| Final Demand | Final Demand | Final Demand Core SA | Final Demand Core NSA | |
| May 2018 | 0.5 | 3.1 | 0.3 | 2.4 |
| Apr | 0.1 | 2.6 | 0.2 | 2.3 |
| AE ∆% Apr-May | 3.7 | 3.0 | ||
| Mar | 0.3 | 3.0 | 0.3 | 2.7 |
| Feb | 0.2 | 2.8 | 0.3 | 2.5 |
| Jan | 0.5 | 2.6 | 0.4 | 2.2 |
| AE ∆% Jan-Mar | 4.1 | 4.1 | ||
| Dec 2017 | 0.0 | 2.5 | -0.1 | 2.2 |
| AE ∆% Dec | 0.0 | -1.2 | ||
| Nov | 0.4 | 3.0 | 0.2 | 2.3 |
| Oct | 0.4 | 2.8 | 0.4 | 2.4 |
| Sep | 0.3 | 2.6 | 0.1 | 2.2 |
| Aug | 0.3 | 2.4 | 0.2 | 2.2 |
| AE ∆% Aug-Nov | 4.3 | 2.7 | ||
| Jul | 0.1 | 2.0 | 0.2 | 1.9 |
| AE ∆% Jul | 1.2 | 2.4 | ||
| Jun | 0.1 | 1.9 | 0.0 | 1.8 |
| May | 0.1 | 2.3 | 0.3 | 2.0 |
| AE ∆% May-Jun | 1.2 | 1.8 | ||
| Apr | 0.4 | 2.5 | 0.4 | 1.9 |
| AE ∆% Apr | 4.9 | 4.9 | ||
| Mar | 0.1 | 2.2 | 0.2 | 1.5 |
| AE ∆% Mar | 1.2 | 2.4 | ||
| Feb | -0.1 | 2.0 | -0.1 | 1.3 |
| AE ∆% Feb | -1.2 | -1.2 | ||
| Jan | 0.5 | 1.7 | 0.4 | 1.4 |
| AE ∆% Jan | 6.2 | 4.9 | ||
| Dec 2016 | 0.4 | 1.7 | 0.1 | 1.7 |
| Nov | 0.1 | 1.3 | 0.2 | 1.7 |
| AE ∆% Nov-Dec | 3.0 | 1.8 | ||
| Oct | 0.3 | 1.1 | 0.2 | 1.5 |
| AE ∆% Oct | 3.7 | 2.4 | ||
| Sep | 0.3 | 0.6 | 0.2 | 1.2 |
| AE ∆% Sep | 3.7 | 2.4 | ||
| Aug | -0.3 | 0.0 | -0.1 | 1.0 |
| AE ∆% Aug | -3.5 | -1.2 | ||
| July | 0.0 | 0.0 | 0.0 | 0.9 |
| AE ∆% Jul | 0.0 | 0.0 | ||
| Jun | 0.5 | 0.2 | 0.3 | 1.2 |
| May | 0.3 | 0.0 | 0.1 | 1.2 |
| Apr | 0.2 | 0.2 | 0.2 | 1.1 |
| AE ∆% Apr-Jun | 4.1 | 2.4 | ||
| Mar | -0.1 | -0.1 | -0.1 | 1.1 |
| Feb | -0.3 | 0.1 | 0.0 | 1.3 |
| AE ∆% Mar-Feb | -2.4 | -0.6 | ||
| Jan | 0.5 | 0.0 | 0.5 | 0.8 |
| AE ∆% Jan | 6.2 | 6.2 | ||
| Dec 2015 | -0.2 | -1.1 | 0.2 | 0.2 |
| AE ∆% Dec | -2.4 | 2.4 | ||
| Nov | 0.1 | -1.3 | 0.1 | 0.3 |
| AE ∆% Nov | 1.2 | 1.2 | ||
| Oct | -0.2 | -1.4 | -0.2 | 0.2 |
| Sep | -0.5 | -1.1 | -0.1 | 0.7 |
| AE ∆% Sep-Oct | -4.1 | -1.8 | ||
| Aug | -0.2 | -1.0 | 0.0 | 0.6 |
| AE ∆% Aug | -2.4 | 0.0 | ||
| Jul | 0.1 | -0.7 | 0.2 | 0.8 |
| Jun | 0.3 | -0.5 | 0.3 | 1.1 |
| May | 0.5 | -0.8 | 0.0 | 0.7 |
| AE ∆% May-Jul | 3.7 | 2.0 | ||
| Apr | -0.1 | -1.1 | 0.2 | 1.0 |
| AE ∆% Apr | -1.2 | 2.4 | ||
| Mar | 0.1 | -0.9 | 0.0 | 0.8 |
| AE ∆% Mar | 1.2 | 0.0 | ||
| Feb | -0.5 | -0.5 | -0.4 | 1.0 |
| Jan | -0.6 | 0.0 | 0.0 | 1.7 |
| AE ∆% Jan-Feb | -6.4 | -2.4 | ||
| Dec 2014 | -0.3 | 0.9 | 0.2 | 2.0 |
| Nov | -0.2 | 1.3 | 0.0 | 1.7 |
| AE ∆% Nov-Dec | -3.0 | 1.2 | ||
| Oct | 0.2 | 1.5 | 0.4 | 1.9 |
| AE ∆% Oct | 2.4 | 4.9 | ||
| Sep | -0.2 | 1.6 | -0.1 | 1.6 |
| Aug | 0.0 | 1.9 | 0.0 | 1.9 |
| AE ∆% Aug-Sep | -1.2 | -0.6 | ||
| Jul | 0.3 | 1.9 | 0.5 | 1.9 |
| Jun | 0.0 | 1.8 | 0.0 | 1.6 |
| May | 0.2 | 2.1 | 0.3 | 2.1 |
| Apr | 0.1 | 1.8 | 0.0 | 1.5 |
| Mar | 0.4 | 1.6 | 0.3 | 1.6 |
| AE ∆% Mar-Jul | 2.4 | 2.7 | ||
| Feb | 0.2 | 1.2 | 0.2 | 1.6 |
| Jan | 0.3 | 1.3 | 0.2 | 1.4 |
| Dec 2013 | 0.1 | 1.2 | 0.0 | 1.2 |
| AE ∆% Dec-Feb | 2.4 | 1.6 | ||
| Nov | 0.2 | 1.1 | 0.2 | 1.4 |
| Oct | 0.2 | 1.3 | 0.2 | 1.7 |
| Sep | 0.0 | 1.1 | 0.1 | 1.6 |
| AE ∆% Sep-Nov | 1.6 | 2.0 | ||
| Aug | 0.1 | 1.7 | 0.0 | 1.8 |
| Jul | 0.2 | 2.0 | 0.3 | 1.7 |
| Jun | 0.4 | 1.7 | 0.4 | 1.3 |
| May | -0.1 | 0.9 | -0.3 | 0.9 |
| AE ∆% May-Aug | 1.8 | 1.6 | ||
| Apr | -0.2 | 0.9 | 0.2 | 1.3 |
| Mar | 0.0 | 1.3 | 0.2 | 1.5 |
| AE ∆% Mar-Apr | -1.2 | 2.4 | ||
| Feb | 0.2 | 1.6 | 0.0 | 1.4 |
| Jan | 0.3 | 1.6 | 0.1 | 1.7 |
| AE ∆% Jan-Feb | 3.0 | 0.6 | ||
| Dec 2012 | 0.0 | 1.9 | 0.1 | 2.0 |
| Nov | 0.1 | 1.7 | 0.5 | 1.8 |
| Oct | 0.1 | 1.9 | 0.1 | 1.6 |
| AE ∆% Oct-Dec | 0.8 | 2.8 | ||
| Sep | 0.7 | 1.5 | 0.3 | 1.4 |
| Aug | 0.3 | 1.2 | -0.1 | 1.2 |
| AE ∆% Aug-Sep | 6.2 | 1.2 | ||
| Jul | -0.1 | 1.0 | -0.1 | 1.7 |
| Jun | -0.3 | 1.3 | -0.1 | 1.9 |
| AE ∆% Jun-Jul | -2.4 | -1.2 | ||
| May | -0.1 | 1.6 | 0.2 | 2.2 |
| Apr | 0.3 | 2.0 | 0.3 | 2.1 |
| AE ∆% Apr-May | 1.2 | 3.0 | ||
| Mar | 0.2 | 2.4 | 0.2 | 2.3 |
| Feb | 0.3 | 2.8 | 0.3 | 2.6 |
| Jan | 0.4 | 3.1 | 0.4 | 2.5 |
| AE ∆% Jan-Mar | 3.7 | 3.7 | ||
| Dec 2011 | -0.1 | 3.2 | 0.0 | 2.6 |
| Nov | 0.3 | 3.7 | 0.2 | 2.7 |
| Oct | -0.4 | 3.7 | -0.3 | 2.7 |
| AE ∆% Oct-Dec | -0.8 | -0.4 | ||
| Sep | 0.4 | 4.5 | 0.2 | 2.9 |
| Aug | 0.2 | 4.4 | 0.4 | 3.0 |
| Jul | 0.2 | 4.5 | 0.2 | 2.7 |
| AE ∆% Jul-Sep | 3.2 | 3.2 | ||
| Jun | 0.1 | 4.3 | 0.2 | 2.6 |
| May | 0.3 | 4.2 | 0.2 | 2.3 |
| AE ∆% May-Jun | 2.4 | 2.4 | ||
| Apr | 0.5 | 4.2 | 0.3 | 2.5 |
| Mar | 0.7 | 4.0 | 0.5 | NA |
| Feb | 0.6 | 3.3 | 0.3 | NA |
| Jan | 0.6 | 2.4 | 0.4 | NA |
| AE ∆% Jan-Apr | 7.4 | 4.6 | ||
| Dec 2010 | 0.3 | 2.8 | 0.1 | NA |
| Nov | 0.3 | 2.6 | 0.1 | NA |
| Oct | 0.4 | NA | 0.1 | NA |
| Sep | 0.3 | NA | 0.2 | NA |
| Aug | 0.2 | NA | 0.0 | NA |
| Jul | 0.2 | NA | 0.2 | NA |
| Jun | -0.2 | NA | -0.1 | NA |
| May | 0.2 | NA | 0.3 | NA |
| Apr | 0.3 | NA | NA | NA |
| Mar | 0.1 | NA | NA | NA |
| Feb | -0.2 | NA | NA | NA |
| Jan | 0.9 | NA | NA | NA |
| Dec 2009 | 0.1 |
Note: Core: excluding food and energy; AE: annual equivalent
Source: US Bureau of Labor Statistics http://www.bls.gov/ppi/data.htm
Chart I-24B provides the FD PPI NSA from 2009 to 2018. There is persistent inflation with periodic declines in inflation waves similar to those worldwide.
Chart I-24B, US, Final Demand Producer Price Index, NSA, 2009-2018
Source: US Bureau of Labor Statistics
Twelve-month percentage changes of the FD PPI from 2010 to 2018 are in Chart I-25B. There are fluctuations in the rates with evident trend of decline to more subdued inflation. Reallocations of investment portfolios of risk financial assets from commodities to stocks explain much lower FD PPI inflation.
Chart I-25B, US, Final Demand Producer Price Index, 12-Month Percentage Change NSA, 2010-2018
Source: US Bureau of Labor Statistics
The core FD PPI NSA is in Chart I-26B. The behavior is similar to the headline index but with less fluctuation.
Chart I-26B, US, Final Demand Producer Price Index Excluding Food and Energy, NSA, 2009-2018
Source: US Bureau of Labor Statistics
Percentage changes in 12 months of the core FD PPI are in Chart I-27B. There are fluctuations in 12-month percentage changes but with evident declining trend to more moderate inflation.
Chart I-27B, US, Final Demand Producer Price Index Excluding Food and Energy, 12-Month Percentage Change, NSA, 2010-2018
Source: US Bureau of Labor Statistics
The energy FD PPI NSA is in Chart I-28B. The index increased during the reposition of carry trades after the discovery of lack of toxic assets in banks that caused flight away from risk financial assets into government obligations of the US (Cochrane and Zingales 2009). Alternating risk aversion and appetite with reallocations among classes of risk financial assets explain the behavior of the index after late 2010.
Chart I-28B, US, Final Demand Energy Producer Price Index, NSA, 2009-2018
Source: US Bureau of Labor Statistics
Twelve-month percentage changes of the FD energy PPI are in Chart I-29B. Rates moderated from late 2010 to the present. There are multiple negative rates. Investors create and reverse carry trades from zero interest rates to derivatives of commodities in accordance with relative risk evaluations of classes of risk financial assets.
Chart I-29B, US, Final Demand Energy Producer Price Index, 12-Month Percentage Change, NSA, 2010-2018
Source: US Bureau of Labor Statistics
Table I-7 provides 12-month percentage changes of the CPI all items, CPI core and CPI housing from 2001 to 2018. There is no evidence in these data supporting symmetric inflation targets that would only induce greater instability in inflation, interest rates and financial markets. 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 (1.99, 2.0). Symmetric targets appear to have been abandoned in a favor of a self-imposed single jobs mandate of easing
monetary policy even with the economy growing at or close to potential output.
Table I-7, CPI All Items, CPI Core and CPI Housing, 12-Month Percentage Change, NSA 2001-2018
| May | CPI All Items | CPI Core ex Food and Energy | CPI Housing |
| 2018 | 2.8 | 2.2 | 3.0 |
| 2017 | 1.9 | 1.7 | 3.1 |
| 2016 | 1.0 | 2.2 | 2.4 |
| 2015 | 0.0 | 1.7 | 1.9 |
| 2014 | 2.1 | 2.0 | 2.6 |
| 2013 | 1.4 | 1.7 | 2.2 |
| 2012 | 1.7 | 2.3 | 1.6 |
| 2011 | 3.6 | 1.5 | 1.2 |
| 2010 | 2.0 | 0.9 | -0.5 |
| 2009 | -1.3 | 1.8 | 0.5 |
| 2008 | 4.2 | 2.3 | 3.3 |
| 2007 | 2.7 | 2.2 | 3.3 |
| 2006 | 4.2 | 2.4 | 4.0 |
| 2005 | 2.8 | 2.2 | 3.0 |
| 2004 | 3.1 | 1.7 | 2.4 |
| 2003 | 2.1 | 1.6 | 2.7 |
| 2002 | 1.2 | 2.5 | 2.2 |
| 2001 | 3.6 | 2.5 | 4.6 |
Source: US Bureau of Labor Statistics http://www.bls.gov/cpi/
II Rules, Discretionary Authorities and Slow Productivity Growth. The Bureau of Labor Statistics (BLS) of the Department of Labor provides the quarterly report on productivity and costs. The operational definition of productivity used by the BLS is (https://www.bls.gov/news.release/pdf/prod2.pdf 1): “Labor productivity, or output per hour, is calculated by dividing an index of real output by an index of hours worked of all persons, including employees, proprietors, and unpaid family workers.” The BLS has revised the estimates for productivity and unit costs. Table II-1 provides the third estimate for IQ2018 and revision of the estimates for IVQ2017 and IIIQ2017 together with data for nonfarm business sector productivity and unit labor costs in seasonally adjusted annual equivalent (SAAE) rate and the percentage change from the same quarter a year earlier. Reflecting increase in output at 2.7 percent and increase at 2.3 percent in hours worked, nonfarm business sector labor productivity changed at the SAAE rate of 0.4 percent in IQ2018, as shown in column 2 “IQ2018 SAEE.” The increase of labor productivity from IQ2017 to IQ2018 was 1.3 percent, reflecting increases in output of 3.6 percent and of hours worked of 2.3 percent, as shown in column 3 “IQ2018 YoY.” Hours worked increased from 1.3 percent in IIIQ2017 at SAAE to 3.3 percent in IVQ2017 and decreased to 2.3 percent in IQ2018 while output growth decreased from 4.0 percent in IIIQ2017 at SAAE to 3.7 percent in IVQ2017, decreasing to 2.7 percent in IQ2018. The BLS defines unit labor costs as (https://www.bls.gov/news.release/pdf/prod2.pdf 1): “BLS calculates unit labor costs as the ratio of hourly compensation to labor productivity. Increases in hourly compensation tend to increase unit labor costs and increases in output per hour tend to reduce them.” Unit labor costs increased at the SAAE rate of 2.9 percent in IQ2018 and increased 1.3 percent in IQ2018 relative to IQ2017. Hourly compensation increased at the SAAE rate of 3.3 percent in IQ2018, which deflating by the estimated consumer price increase SAAE rate in IQ2018 results in decrease of real hourly compensation at 0.2 percent. Real hourly compensation increased 0.3 percent in IQ2018 relative to IQ2017.
Table II-1, US, Nonfarm Business Sector Productivity and Costs %
| IQ2018 SAAE | IQ2018 YOY | IVQ2017 SAAE | IVQ2017 YOY | IIIQ2017 SAAE | IIIQ 2017 YOY | |
| Productivity | 0.4 | 1.3 | 0.3 | 1.2 | 2.6 | 1.4 |
| Output | 2.7 | 3.6 | 3.7 | 3.3 | 4.0 | 3.0 |
| Hours | 2.3 | 2.3 | 3.3 | 2.1 | 1.3 | 1.5 |
| Hourly | 3.3 | 2.6 | 2.9 | 3.0 | 3.6 | 1.1 |
| Real Hourly Comp. | -0.2 | 0.3 | -0.4 | 0.9 | 1.5 | -0.9 |
| Unit Labor Costs | 2.9 | 1.3 | 2.5 | 1.8 | 1.0 | -0.4 |
| Unit Nonlabor Payments | -0.4 | 2.1 | 2.3 | 1.2 | 3.5 | 3.9 |
| Implicit Price Deflator | 1.5 | 1.6 | 2.4 | 1.5 | 2.0 | 1.5 |
Notes: SAAE: seasonally adjusted annual equivalent; Comp.: compensation; YoY: Quarter on Same Quarter Year Earlier
The analysis by Kydland (http://www.nobelprize.org/nobel_prizes/economic-sciences/laureates/2004/kydland-bio.html) and Prescott (http://www.nobelprize.org/nobel_prizes/economic-sciences/laureates/2004/prescott-bio.html) (1977, 447-80, equation 5) uses the “expectation augmented” Phillips curve with the natural rate of unemployment of Friedman (1968) and Phelps (1968), which in the notation of Barro and Gordon (1983, 592, equation 1) is:
Ut = Unt – α(πt – πe) α > 0 (1)
Where Ut is the rate of unemployment at current time t, Unt is the natural rate of unemployment, πt is the current rate of inflation and πe is the expected rate of inflation by economic agents based on current information. Equation (1) expresses unemployment net of the natural rate of unemployment as a decreasing function of the gap between actual and expected rates of inflation. The system is completed by a social objective function, W, depending on inflation, π, and unemployment, U:
W = W(πt, Ut) (2)
The policymaker maximizes the preferences of the public, (2), subject to the constraint of the tradeoff of inflation and unemployment, (1). The total differential of W set equal to zero provides an indifference map in the Cartesian plane with ordered pairs (πt, Ut - Un) such that the consistent equilibrium is found at the tangency of an indifference curve and the Phillips curve in (1). The indifference curves are concave to the origin. The consistent policy is not optimal. Policymakers without discretionary powers following a rule of price stability would attain equilibrium with unemployment not higher than with the consistent policy. The optimal outcome is obtained by the rule of price stability, or zero inflation, and no more unemployment than under the consistent policy with nonzero inflation and the same unemployment. Taylor (1998LB) attributes the sustained boom of the US economy after the stagflation of the 1970s to following a monetary policy rule instead of discretion (see Taylor 1993, 1999). Professor John B. Taylor (2014Jul15, 2014Jun26) building on advanced research (Taylor 2007, 2008Nov, 2009, 2012FP, 2012Mar27, 2012Mar28, 2012JMCB, 2015, 2012 Oct 25; 2013Oct28, 2014 Jan01, 2014Jan3, 2014Jun26, 2014Jul15, 2015, 2016Dec7, 2016Dec20 http://www.johnbtaylor.com/) finds that a monetary policy rule would function best in promoting an environment of low inflation and strong economic growth with stability of financial markets. There is strong case for using rules instead of discretionary authorities in monetary policy (http://cmpassocregulationblog.blogspot.com/2017/01/rules-versus-discretionary-authorities.html and earlier http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html). It is not uncommon for effects of regulation differing from those intended by policy. Professors Edward C. Prescott and Lee E. Ohanian (2014Feb), writing on “US productivity growth has taken a dive,” on Feb 3, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702303942404579362462611843696?KEYWORDS=Prescott), argue that impressive productivity growth over the long-term constructed US prosperity and wellbeing. Prescott and Ohanian (2014Feb) measure US productivity growth at 2.5 percent per year since 1948. Average US productivity growth has been only 1.1 percent since 2011. Prescott and Ohanian (2014Feb) argue that living standards in the US increased at 28 percent in a decade but with current slow growth of productivity will only increase 12 percent by 2024. There may be collateral effects on productivity growth from policy design similar to those in Kydland and Prescott (1977). Professor Edward P. Lazear (2017Feb27), writing in the Wall Street Journal, on Feb 27, 2017 (https://www.wsj.com/articles/how-trump-can-hit-3-growthmaybe-1488239746), finds that productivity growth was 7 percent between 2009 and 2016 at annual equivalent 1 percent. Lazear measures productivity growth at 2.3 percent per year from 2001 to 2008. Herkenhoff, Ohanian and Prescott (2017) and Ohanian and Prescott (2017Dec) analyze how restriction of land use by states in the United States have been depressing economic activity. The Bureau of Labor Statistics important report on productivity and costs released on Feb 1, 2018 (http://www.bls.gov/lpc/) supports the argument of decline of productivity growth in the US analyzed by Prescott and Ohanian (2014Feb) and Lazear (2017Feb27). Table II-2 provides the annual percentage changes of productivity, real hourly compensation and unit labor costs for the entire economic cycle from 2007 to 2017. The estimates incorporate the yearly revision of the US national accounts (https://www.bea.gov/scb/pdf/2017/08-August/0817-2017-annual-nipa-update.pdf). The data confirm the argument of Prescott and Ohanian (2014Feb) and Lazear (2017Feb27): productivity increased cumulatively 4.9 percent from 2011 to 2017 at the average annual rate of 0.7 percent. The situation is direr by excluding growth of 0.9 percent in 2012, which leaves an average of 0.6 percent for 2011-2017. Average productivity growth for the entire economic cycle from 2007 to 2017 is only 1.2 percent. The argument by Prescott and Ohanian (2014Feb) is proper in choosing the tail of the business cycle because the increase in productivity in 2009 of 3.1 percent and 3.3 percent in 2010 consisted of reducing labor hours.
Table II-2, US, Revised Nonfarm Business Sector Productivity and Costs Annual Average, ∆% Annual Average
| 2017 ∆% | ||||||
| Productivity | 1.3 | |||||
| Real Hourly Compensation | -0.5 | |||||
| Unit Labor Costs | 0.4 | |||||
| 2016 ∆% | 2015 ∆% | 2014 ∆% | 2013 ∆% | 2012 ∆% | 2011 ∆% | |
| Productivity | 0.0 | 1.2 | 1.0 | 0.3 | 0.9 | 0.1 |
| Real Hourly Compensation | -0.2 | 2.9 | 1.1 | -0.3 | 0.5 | -0.9 |
| Unit Labor Costs | 1.1 | 1.8 | 1.9 | 0.9 | 1.7 | 2.1 |
| 2010 ∆% | 2009 ∆% | 2008 ∆% | 2007∆% | |
| Productivity | 3.3 | 3.1 | 0.8 | 1.6 |
| Real Hourly Compensation | 0.3 | 1.4 | -1.0 | 1.4 |
| Unit Labor Costs | -1.3 | -2.0 | 2.0 | 2.7 |
Source: US Bureau of Labor Statistics
Productivity jumped in the recovery after the recession from Mar IQ2001 to Nov IVQ2001 (http://www.nber.org/cycles.html) Table II-3 provides quarter on quarter and annual percentage changes in nonfarm business output per hour, or productivity, from 1999 to 2018. The annual average jumped from 2.7 percent in 2001 to 4.4 percent in 2002. Nonfarm business productivity increased at the SAAE rate of 9.4 percent in the first quarter after the recession in IQ2002. Productivity increases decline later in the expansion period. Productivity increases were mediocre during the recession from Dec IVQ2007 to Jun IIIQ2009 (http://www.nber.org/cycles.html) and increased during the first phase of expansion from IIQ2009 to IQ2010, trended lower and collapsed in 2011 and 2012 with sporadic jumps and declines. Productivity increased at 4.1 percent in IVQ2013 and contracted at 3.2 percent in IQ2014. Productivity increased at 2.5 percent in IIQ2014 and at 4.2 percent in IIIQ2014. Productivity contracted at 2.1 percent in IVQ2014 and increased at 3.0 percent in IQ2015. Productivity grew at 1.3 percent in IIQ2015 and increased at 1.2 percent in IIIQ2015. Productivity contracted at 2.7 percent in IVQ2015 and contracted at 1.1 percent in IQ2016. Productivity increased at 1.0 percent in IIQ2016 and expanded at 2.4 percent in IIIQ2016. Productivity grew at 1.2 percent in IVQ2016 and increased at 0.2 percent in IQ2017. Productivity increased at 1.7 percent in IIQ2017 and increased at 2.6 percent in IIIQ2017. Productivity increased at 0.3 percent in IVQ2017 and increased at 0.4 percent in IQ2018.
Table II-3, US, Nonfarm Business Output per Hour, Percent Change from Prior Quarter at Annual Rate, 1999-2018
| Year | Qtr1 | Qtr2 | Qtr3 | Qtr4 | Annual |
| 1999 | 4.4 | 1.2 | 3.5 | 6.6 | 3.7 |
| 2000 | -1.9 | 8.2 | -0.2 | 4.1 | 3.0 |
| 2001 | -1.6 | 7.0 | 2.1 | 5.2 | 2.7 |
| 2002 | 9.4 | 0.2 | 3.1 | -0.6 | 4.4 |
| 2003 | 4.1 | 5.4 | 9.0 | 4.0 | 3.7 |
| 2004 | -0.1 | 3.8 | 1.4 | 1.3 | 3.1 |
| 2005 | 4.5 | -0.4 | 3.0 | 0.2 | 2.1 |
| 2006 | 2.4 | -0.4 | -1.7 | 3.0 | 0.9 |
| 2007 | 0.4 | 2.5 | 4.9 | 1.7 | 1.6 |
| 2008 | -3.8 | 4.1 | 1.1 | -2.6 | 0.8 |
| 2009 | 3.0 | 8.0 | 5.8 | 4.9 | 3.1 |
| 2010 | 2.1 | 1.4 | 2.0 | 1.7 | 3.3 |
| 2011 | -3.3 | 1.3 | -0.7 | 2.8 | 0.1 |
| 2012 | 0.6 | 2.3 | -0.8 | -1.7 | 0.9 |
| 2013 | 0.9 | -0.6 | 1.6 | 4.1 | 0.3 |
| 2014 | -3.2 | 2.5 | 4.2 | -2.1 | 1.0 |
| 2015 | 3.0 | 1.3 | 1.2 | -2.7 | 1.2 |
| 2016 | -1.1 | 1.0 | 2.4 | 1.2 | 0.0 |
| 2017 | 0.2 | 1.7 | 2.6 | 0.3 | 1.3 |
| 2018 | 0.4 |
Source: US Bureau of Labor Statistics http://www.bls.gov/lpc/
Chart II-1, US, Nonfarm Business Output per Hour, Percent Change from Prior Quarter at Annual Rate, 1999-2018
Source: US Bureau of Labor Statistics http://www.bls.gov/lpc/
Percentage changes from prior quarter at SAAE rates and annual average percentage changes of nonfarm business unit labor costs are provided in Table II-4. Unit labor costs fell during the contractions with continuing negative percentage changes in the early phases of the recovery. Weak labor markets partly explain the decline in unit labor costs. As the economy moves toward full employment, labor markets tighten with increase in unit labor costs. The expansion beginning in IIIQ2009 has been characterized by high unemployment and underemployment. Table II-4 shows continuing subdued increases in unit labor costs in 2011 but with increase at 8.9 percent in IQ2012 followed by decrease at 0.1 percent in IIQ2012, increase at 1.1 percent in IIIQ2012 and increase at 13.2 percent in IVQ2012. Unit labor costs decreased at 9.7 percent in IQ2013 and increased at 6.5 percent in IIQ2013. Unit labor costs decreased at 0.5 percent in IIIQ2013 and decreased at 1.9 percent in IVQ2013. Unit labor costs increased at 10.6 percent in IQ2014 and at minus 4.7 percent in IIQ2014. Unit labor costs decreased at 1.2 percent in IIIQ2014 and increased at 7.1 percent in IVQ2014. Unit labor costs increased at 0.6 percent in IQ2015 and increased at 2.3 percent in IIQ2015. Unit labor costs decreased at 0.2 percent in IIIQ2015 and increased at 7.2 percent in IVQ2015. Unit labor costs decreased at 2.6 percent in IQ2016 and increased at 3.9 percent in IIQ2016. Unit labor costs changed at 0.0 percent in IIIQ2016 and decreased at 5.7 percent in IVQ2016. Unit labor costs increased at 4.8 percent in IQ2017 and decreased at 1.2 percent in IIQ2017. United labor costs increased at 1.0 percent in IIIQ2017 and increased at 2.5 percent in IVQ2017. Unit labor costs increased at 2.9 percent in IQ2018.
Table II-4, US, Nonfarm Business Unit Labor Costs, Percent Change from Prior Quarter at Annual Rate 1999-2018
| Year | Qtr1 | Qtr2 | Qtr3 | Qtr4 | Annual |
| 1999 | 2.8 | 0.3 | 0.0 | 1.7 | 0.9 |
| 2000 | 17.4 | -6.8 | 8.2 | -1.7 | 4.0 |
| 2001 | 11.4 | -5.4 | -1.7 | -1.4 | 1.6 |
| 2002 | -6.6 | 3.3 | -1.1 | 1.7 | -2.0 |
| 2003 | -1.5 | 1.6 | -2.6 | 1.5 | 0.1 |
| 2004 | -0.5 | 3.9 | 5.7 | 0.5 | 1.4 |
| 2005 | -1.3 | 2.6 | 1.9 | 2.3 | 1.6 |
| 2006 | 6.1 | 0.5 | 2.3 | 4.0 | 3.0 |
| 2007 | 9.8 | -2.7 | -3.2 | 2.6 | 2.7 |
| 2008 | 8.3 | -3.5 | 2.4 | 7.1 | 2.0 |
| 2009 | -12.3 | 2.1 | -3.0 | -2.3 | -2.0 |
| 2010 | -4.8 | 3.2 | -0.2 | 0.2 | -1.3 |
| 2011 | 11.0 | -3.5 | 3.3 | -7.7 | 2.1 |
| 2012 | 8.9 | -0.1 | 1.1 | 13.2 | 1.7 |
| 2013 | -9.7 | 6.5 | -0.5 | -1.9 | 0.9 |
| 2014 | 10.6 | -4.7 | -1.2 | 7.1 | 1.9 |
| 2015 | 0.6 | 2.3 | -0.2 | 7.2 | 1.8 |
| 2016 | -2.6 | 3.9 | 0.0 | -5.7 | 1.1 |
| 2017 | 4.8 | -1.2 | 1.0 | 2.5 | 0.4 |
| 2018 | 2.9 |
Source: US Bureau of Labor Statistics http://www.bls.gov/lpc/
Chart II-2 provides change of unit labor costs at SAAE from 1999 to 2018. There are multiple oscillations recently with negative changes alternating with positive changes.
Chart II-2, US, Nonfarm Business Unit Labor Costs, Percent Change from Prior Quarter at Annual Rate 1999-2018
Source: US Bureau of Labor Statistics http://www.bls.gov/lpc/
Table II-5 provides percentage change from prior quarter at annual rates for nonfarm business real hourly worker compensation. The expansion after the contraction of 2001 was followed by strong recovery of real hourly compensation. Real hourly compensation increased at the rate of 2.9 percent in IQ2011 but fell at annual rates of 6.6 percent in IIQ2011 and 6.9 percent in IVQ2011. Real hourly compensation increased at 7.0 percent in IQ2012, increasing at 1.4 percent in IIQ2012, declining at 1.6 percent in IIIQ2012 and increasing at 8.4 percent in IVQ2012. Real hourly compensation fell at 0.9 percent in 2011 and increased at 0.5 percent in 2012. Real hourly compensation fell at 10.4 percent in IQ2013 and increased at 6.2 percent in IIQ2013, falling at 1.1 percent in IIIQ2013. Real hourly compensation increased at 0.6 percent in IVQ2013 and at 4.3 percent in IQ2014. Real hourly compensation decreased at 4.3 percent in IIQ2014. Real hourly compensation increased at 1.8 percent in IIIQ2014. The annual rate of increase of real hourly compensation for 2013 is minus 0.3 percent. Real hourly compensation increased at 5.7 percent in IVQ2014. The annual rate of increase of real hourly compensation in 2014 is 1.1 percent. Real hourly compensation increased at 6.3 percent in IQ2015 and increased at 0.9 percent in IIQ2015. Real hourly compensation decreased at 0.6 percent in IIIQ2015 and increased at 4.1 percent in IVQ2015. Real hourly compensation increased at 2.9 percent in 2015. Real hourly compensation decreased at 3.6 percent in IQ2016 and increased at 2.1 percent in IIQ2016. Real hourly compensation increased at 0.6 percent in IIIQ2016 and decreased at 7.1 percent in IVQ2016. Real hourly compensation decreased 0.2 percent in 2016. Real hourly compensation increased at 2.0 percent in IQ2017 and increased at 0.4 percent in IIQ2017. Real hourly compensation increased at 1.5 percent in IIIQ2017. Real hourly compensation decreased at 0.4 percent in IVQ2017. Real hourly compensation fell 0.5 percent in 2017. Real hourly compensation fell at 0.2 percent in IQ2018.
Table II-5, Nonfarm Business Real Hourly Compensation, Percent Change from Prior Quarter at Annual Rate 1999-2018
| Year | Qtr1 | Qtr2 | Qtr3 | Qtr4 | Annual |
| 1999 | 5.9 | -1.5 | 0.5 | 5.1 | 2.5 |
| 2000 | 10.6 | -2.2 | 4.1 | -0.5 | 3.5 |
| 2001 | 5.4 | -1.7 | -0.7 | 4.1 | 1.4 |
| 2002 | 0.8 | 0.3 | -0.2 | -1.2 | 0.7 |
| 2003 | -1.5 | 7.7 | 3.0 | 3.9 | 1.5 |
| 2004 | -3.9 | 4.6 | 4.5 | -2.6 | 1.8 |
| 2005 | 1.1 | -0.6 | -1.1 | -1.3 | 0.3 |
| 2006 | 6.4 | -3.5 | -3.1 | 8.8 | 0.6 |
| 2007 | 6.0 | -4.6 | -1.0 | -0.5 | 1.4 |
| 2008 | -0.3 | -4.7 | -2.6 | 14.5 | -1.0 |
| 2009 | -7.1 | 7.9 | -0.8 | -0.7 | 1.4 |
| 2010 | -3.3 | 4.8 | 0.5 | -1.3 | 0.3 |
| 2011 | 2.9 | -6.6 | -0.1 | -6.9 | -0.9 |
| 2012 | 7.0 | 1.4 | -1.6 | 8.4 | 0.5 |
| 2013 | -10.4 | 6.2 | -1.1 | 0.6 | -0.3 |
| 2014 | 4.3 | -4.3 | 1.8 | 5.7 | 1.1 |
| 2015 | 6.3 | 0.9 | -0.6 | 4.1 | 2.9 |
| 2016 | -3.6 | 2.1 | 0.6 | -7.1 | -0.2 |
| 2017 | 2.0 | 0.4 | 1.5 | -0.4 | -0.5 |
| 2018 | -0.2 |
Source: US Bureau of Labor Statistics http://www.bls.gov/lpc/
Chart II-3, US, Nonfarm Business Real Hourly Compensation, Percent Change from Prior Quarter at Annual Rate 1999-2018
Source: US Bureau of Labor Statistics http://www.bls.gov/lpc/
Chart II-4 provides percentage change of nonfarm business output per hour in a quarter relative to the same quarter a year earlier. As in most series of real output, productivity increased sharply in 2010 but the momentum was lost after 2011 as with the rest of the real economy.
Chart II-4, US, Nonfarm Business Output per Hour, Percent Change from Same Quarter a Year Earlier 1999-2018
Source: US Bureau of Labor Statistics http://www.bls.gov/lpc/
Chart II-5 provides percentage changes of nonfarm business unit labor costs relative to the same quarter a year earlier. Softening of labor markets caused relatively high yearly percentage changes in the recession of 2001 repeated in the recession in 2009. Recovery was strong in 2010 but then weakened.
Chart II-5, US, Nonfarm Business Unit Labor Costs, Percent Change from Same Quarter a Year Earlier 1999-2018
Source: US Bureau of Labor Statistics http://www.bls.gov/lpc/
Chart II-6 provides percentage changes in a quarter relative to the same quarter a year earlier for nonfarm business real hourly compensation. Labor compensation eroded sharply during the recession with brief recovery in 2010 and another fall until recently.
Chart II-6, US, Nonfarm Business Real Hourly Compensation, Percent Change from Same Quarter a Year Earlier 1999-2018
2005=100
Source: US Bureau of Labor Statistics http://www.bls.gov/lpc/
In the analysis of Hansen (1939, 3) of secular stagnation, economic progress consists of growth of real income per person driven by growth of productivity. The “constituent elements” of economic progress are “(a) inventions, (b) the discovery and development of new territory and new resources, and (c) the growth of population” (Hansen 1939, 3). Secular stagnation originates in decline of population growth and discouragement of inventions. According to Hansen (1939, 2), US population grew by 16 million in the 1920s but grew by one half or about 8 million in the 1930s with forecasts at the time of Hansen’s writing in 1938 of growth of around 5.3 million in the 1940s. Hansen (1939, 2) characterized demography in the US as “a drastic decline in the rate of population growth.” Hansen’s plea was to adapt economic policy to stagnation of population in ensuring full employment. In the analysis of Hansen (1939, 8), population caused half of the growth of US GDP per year. Growth of output per person in the US and Europe was caused by “changes in techniques and to the exploitation of new natural resources.” In this analysis, population caused 60 percent of the growth of capital formation in the US. Declining population growth would reduce growth of capital formation. Residential construction provided an important share of growth of capital formation. Hansen (1939, 12) argues that market power of imperfect competition discourages innovation with prolonged use of obsolete capital equipment. Trade unions would oppose labor-savings innovations. The combination of stagnating and aging population with reduced innovation caused secular stagnation. Hansen (1939, 12) concludes that there is role for public investments to compensate for lack of dynamism of private investment but with tough tax/debt issues.
The current application of Hansen’s (1938, 1939, 1941) proposition argues that secular stagnation occurs because full employment equilibrium can be attained only with negative real interest rates between minus 2 and minus 3 percent. Professor Lawrence H. Summers (2013Nov8) finds that “a set of older ideas that went under the phrase secular stagnation are not profoundly important in understanding Japan’s experience in the 1990s and may not be without relevance to America’s experience today” (emphasis added). Summers (2013Nov8) argues there could be an explanation in “that the short-term real interest rate that was consistent with full employment had fallen to -2% or -3% sometime in the middle of the last decade. Then, even with artificial stimulus to demand coming from all this financial imprudence, you wouldn’t see any excess demand. And even with a relative resumption of normal credit conditions, you’d have a lot of difficulty getting back to full employment.” The US economy could be in a situation where negative real rates of interest with fed funds rates close to zero as determined by the Federal Open Market Committee (FOMC) do not move the economy to full employment or full utilization of productive resources. Summers (2013Oct8) finds need of new thinking on “how we manage an economy in which the zero nominal interest rates is a chronic and systemic inhibitor of economy activity holding our economies back to their potential.”
Former US Treasury Secretary Robert Rubin (2014Jan8) finds three major risks in prolonged unconventional monetary policy of zero interest rates and quantitative easing: (1) incentive of delaying action by political leaders; (2) “financial moral hazard” in inducing excessive exposures pursuing higher yields of risker credit classes; and (3) major risks in exiting unconventional policy. Rubin (2014Jan8) proposes reduction of deficits by structural reforms that could promote recovery by improving confidence of business attained with sound fiscal discipline.
Professor John B. Taylor (2014Jan01, 2014Jan3) provides clear thought on the lack of relevance of Hansen’s contention of secular stagnation to current economic conditions. The application of secular stagnation argues that the economy of the US has attained full-employment equilibrium since around 2000 only with negative real rates of interest of minus 2 to minus 3 percent. At low levels of inflation, the so-called full-employment equilibrium of negative interest rates of minus 2 to minus 3 percent cannot be attained and the economy stagnates. Taylor (2014Jan01) analyzes multiple contradictions with current reality in this application of the theory of secular stagnation:
- Secular stagnation would predict idle capacity, in particular in residential investment when fed fund rates were fixed at 1 percent from Jun 2003 to Jun 2004. Taylor (2014Jan01) finds unemployment at 4.4 percent with house prices jumping 7 percent from 2002 to 2003 and 14 percent from 2004 to 2005 before dropping from 2006 to 2007. GDP prices doubled from 1.7 percent to 3.4 percent when interest rates were low from 2003 to 2005.
- Taylor (2014Jan01, 2014Jan3) finds another contradiction in the application of secular stagnation based on low interest rates because of savings glut and lack of investment opportunities. Taylor (2009) shows that there was no savings glut. The savings rate of the US in the past decade is significantly lower than in the 1980s.
- Taylor (2014Jan01, 2014Jan3) finds another contradiction in the low ratio of investment to GDP currently and reduced investment and hiring by US business firms.
- Taylor (2014Jan01, 2014Jan3) argues that the financial crisis and global recession were caused by weak implementation of existing regulation and departure from rules-based policies.
- Taylor (2014Jan01, 2014Jan3) argues that the recovery from the global recession was constrained by a change in the regime of regulation and fiscal/monetary policies.
The analysis by Kydland (http://www.nobelprize.org/nobel_prizes/economic-sciences/laureates/2004/kydland-bio.html) and Prescott (http://www.nobelprize.org/nobel_prizes/economic-sciences/laureates/2004/prescott-bio.html) (1977, 447-80, equation 5) uses the “expectation augmented” Phillips curve with the natural rate of unemployment of Friedman (1968) and Phelps (1968), which in the notation of Barro and Gordon (1983, 592, equation 1) is:
Ut = Unt – α(πt – πe) α > 0 (1)
Where Ut is the rate of unemployment at current time t, Unt is the natural rate of unemployment, πt is the current rate of inflation and πe is the expected rate of inflation by economic agents based on current information. Equation (1) expresses unemployment net of the natural rate of unemployment as a decreasing function of the gap between actual and expected rates of inflation. The system is completed by a social objective function, W, depending on inflation, π, and unemployment, U:
W = W(πt, Ut) (2)
The policymaker maximizes the preferences of the public, (2), subject to the constraint of the tradeoff of inflation and unemployment, (1). The total differential of W set equal to zero provides an indifference map in the Cartesian plane with ordered pairs (πt, Ut - Un) such that the consistent equilibrium is found at the tangency of an indifference curve and the Phillips curve in (1). The indifference curves are concave to the origin. The consistent policy is not optimal. Policymakers without discretionary powers following a rule of price stability would attain equilibrium with unemployment not higher than with the consistent policy. The optimal outcome is obtained by the rule of price stability, or zero inflation, and no more unemployment than under the consistent policy with nonzero inflation and the same unemployment. Taylor (1998LB) attributes the sustained boom of the US economy after the stagflation of the 1970s to following a monetary policy rule instead of discretion (see Taylor 1993, 1999). Professor John B. Taylor (2014Jul15, 2014Jun26) building on advanced research (Taylor 2007, 2008Nov, 2009, 2012FP, 2012Mar27, 2012Mar28, 2012JMCB, 2015, 2012 Oct 25; 2013Oct28, 2014 Jan01, 2014Jan3, 2014Jun26, 2014Jul15, 2015, 2016Dec7, 2016Dec20 http://www.johnbtaylor.com/) finds that a monetary policy rule would function best in promoting an environment of low inflation and strong economic growth with stability of financial markets. There is strong case for using rules instead of discretionary authorities in monetary policy (http://cmpassocregulationblog.blogspot.com/2017/01/rules-versus-discretionary-authorities.html and earlier http://cmpassocregulationblog.blogspot.com/2012/06/rules-versus-discretionary-authorities.html). It is not uncommon for effects of regulation differing from those intended by policy. Professors Edward C. Prescott and Lee E. Ohanian (2014Feb), writing on “US productivity growth has taken a dive,” on Feb 3, 2014, published in the Wall Street Journal (http://online.wsj.com/news/articles/SB10001424052702303942404579362462611843696?KEYWORDS=Prescott), argue that impressive productivity growth over the long-term constructed US prosperity and wellbeing. Prescott and Ohanian (2014Feb) measure US productivity growth at 2.5 percent per year since 1948. Average US productivity growth has been only 1.1 percent since 2011. Prescott and Ohanian (2014Feb) argue that living standards in the US increased at 28 percent in a decade but with current slow growth of productivity will only increase 12 percent by 2024. There may be collateral effects on productivity growth from policy design similar to those in Kydland and Prescott (1977). Professor Edward P. Lazear (2017Feb27), writing in the Wall Street Journal, on Feb 27, 2017 (https://www.wsj.com/articles/how-trump-can-hit-3-growthmaybe-1488239746), finds that productivity growth was 7 percent between 2009 and 20016 at annual equivalent 1 percent. Lazear measures productivity growth at 2.3 percent per year from 2001 to 2008. Herkenhoff, Ohanian and Prescott (2017) and Ohanian and Prescott (2017Dec) analyze how restriction of land use by states in the United States have been depressing economic activity. The Bureau of Labor Statistics important report on productivity and costs released on Mar 8, 2017 (http://www.bls.gov/lpc/) supports the argument of decline of productivity growth in the US analyzed by Prescott and Ohanian (2014Feb) and Lazear (2017Feb27). Table II-2 provides the annual percentage changes of productivity, real hourly compensation and unit labor costs for the entire economic cycle from 2007 to 2017. The estimates incorporate the yearly revision of the US national accounts (https://www.bea.gov/national/an1.htm#2017annualupdate). The data confirm the argument of Prescott and Ohanian (2014Feb) and Lazear (2017Feb27): productivity increased cumulatively 4.9 percent from 2011 to 2017 at the average annual rate of 0.7 percent. The situation is direr by excluding growth of 0.9 percent in 2012, which leaves an average of 0.6 percent for 2011-2017. Average productivity growth for the entire economic cycle from 2007 to 2017 is only 1.2 percent. The argument by Prescott and Ohanian (2014Feb) is proper in choosing the tail of the business cycle because the increase in productivity in 2009 of 3.1 percent and 3.3 percent in 2010 consisted of reducing labor hours.
In revealing research, Edward P. Lazear and James R. Spletzer (2012JHJul22) use the wealth of data in the valuable database and resources of the Bureau of Labor Statistics (http://www.bls.gov/data/) in providing clear thought on the nature of the current labor market of the United States. The critical issue of analysis and policy currently is whether unemployment is structural or cyclical. Structural unemployment could occur because of (1) industrial and demographic shifts and (2) mismatches of skills and job vacancies in industries and locations. Consider the aggregate unemployment rate, Y, expressed in terms of share si of a demographic group in an industry i and unemployment rate yi of that demographic group (Lazear and Spletzer 2012JHJul22, 5-6):
Y = ∑isiyi (1)
This equation can be decomposed for analysis as (Lazear and Spletzer 2012JHJul22, 6):
∆Y = ∑i∆siy*i + ∑i∆yis*i (2)
The first term in (2) captures changes in the demographic and industrial composition of the economy ∆si multiplied by the average rate of unemployment y*i , or structural factors. The second term in (2) captures changes in the unemployment rate specific to a group, or ∆yi, multiplied by the average share of the group s*i, or cyclical factors. There are also mismatches in skills and locations relative to available job vacancies. A simple observation by Lazear and Spletzer (2012JHJul22) casts intuitive doubt on structural factors: the rate of unemployment jumped from 4.4 percent in the spring of 2007 to 10 percent in October 2009. By nature, structural factors should be permanent or occur over relative long periods. The revealing result of the exhaustive research of Lazear and Spletzer (2012JHJul22) is:
“The analysis in this paper and in others that we review do not provide any compelling evidence that there have been changes in the structure of the labor market that are capable of explaining the pattern of persistently high unemployment rates. The evidence points to primarily cyclic factors.”
The theory of secular stagnation cannot explain sudden collapse of the US economy and labor markets. The theory of secular stagnation departs from an aggregate production function in which output grows with the use of labor, capital and technology (see Pelaez and Pelaez, Globalization and the State, Vol. I (2008a), 11-6). Simon Kuznets (1971) analyzes modern economic growth in his Lecture in Memory of Alfred Nobel:
“The major breakthroughs in the advance of human knowledge, those that constituted dominant sources of sustained growth over long periods and spread to a substantial part of the world, may be termed epochal innovations. And the changing course of economic history can perhaps be subdivided into economic epochs, each identified by the epochal innovation with the distinctive characteristics of growth that it generated. Without considering the feasibility of identifying and dating such economic epochs, we may proceed on the working assumption that modern economic growth represents such a distinct epoch - growth dating back to the late eighteenth century and limited (except in significant partial effects) to economically developed countries. These countries, so classified because they have managed to take adequate advantage of the potential of modern technology, include most of Europe, the overseas offshoots of Western Europe, and Japan—barely one quarter of world population.”
Chart II-7 provides nonfarm-business labor productivity, measured by output per hour, from 1947 to 2018. The rate of productivity increase continued in the early part of the 2000s but then softened and fell during the global recession. The interruption of productivity increases occurred exclusively in the current business cycle. Lazear and Spletzer (2012JHJul22) find “primarily cyclic” factors in explaining the frustration of currently depressed labor markets in the United States. Stagnation of productivity is another cyclic event and not secular trend. The theory and application of secular stagnation to current US economic conditions is void of reality.
Chart II-7, US, Nonfarm Business Labor Productivity, Output per Hour, 1947-2018, Index 2009=100
Source: US Bureau of Labor Statistics http://www.bls.gov/lpc/
Table II-6 expands Table II-2 providing more complete measurements of the Productivity and Cost research of the Bureau of Labor Statistics. The proper emphasis of Prescott and Ohanian (2014Feb) is on the low productivity increases from 2011 to 2017. Labor productivity increased 3.3 percent in 2010 and 3.1 percent in 2009. There is much stronger yet not sustained performance in 2010 with productivity growing 3.3 percent because of growth of output of 3.2 percent with decline of hours worked of 0.1 percent. Productivity growth of 3.1 percent in 2009 consists of decline of output by 4.3 percent while hours worked collapsed 7.2 percent, which is not a desirable route to progress. The expansion phase of the economic cycle concentrated in one year, 2010, with underperformance in the remainder of the expansion from 2011 to 2017 of productivity growth at average 0.7 percent per year.
Table II-6, US, Productivity and Costs, Annual Percentage Changes 2007-2017
| 2017 | |||||
| Productivity | 1.3 | ||||
| Output | 2.9 | ||||
| Hours Worked | 1.6 | ||||
| Employment | 1.6 | ||||
| Average Weekly Hours Worked | 0.0 | ||||
| Unit Labor Costs | 0.4 | ||||
| Hourly Compensation | 1.7 | ||||
| Consumer Price Inflation | 2.1 | ||||
| Real Hourly Compensation | -0.5 | ||||
| Non-labor Payments | 6.0 | ||||
| Output per Job | 1.3 | ||||
| 2016 | 2015 | 2014 | 2013 | 2012 | |
| Productivity | 0.0 | 1.2 | 1.0 | 0.3 | 0.9 |
| Output | 1.5 | 3.4 | 3.3 | 2.0 | 3.1 |
| Hours Worked | 1.5 | 2.2 | 2.3 | 1.7 | 2.2 |
| Employment | 1.8 | 2.2 | 2.1 | 1.8 | 2.0 |
| Average Weekly Hours Worked | -0.3 | -0.1 | 0.2 | -0.1 | 0.2 |
| Unit Labor Costs | 1.1 | 1.8 | 1.9 | 0.9 | 1.7 |
| Hourly Compensation | 1.1 | 3.1 | 2.9 | 1.2 | 2.6 |
| Consumer Price Inflation | 1.3 | 0.1 | 1.6 | 1.5 | 2.1 |
| Real Hourly Compensation | -0.2 | 2.9 | 1.1 | -0.3 | 0.5 |
| Non-labor Payments | 2.9 | 3.1 | 4.9 | 4.4 | 5.3 |
| Output per Job | -0.3 | 1.2 | 1.2 | 0.2 | 1.1 |
| 2011 | 2010 | 2009 | 2008 | 2007 | |
| Productivity | 0.1 | 3.3 | 3.1 | 0.8 | 1.6 |
| Output | 2.2 | 3.2 | -4.3 | -1.3 | 2.3 |
| Hours Worked | 2.1 | -0.1 | -7.2 | -2.1 | 0.7 |
| Employment | 1.6 | -1.2 | -5.7 | -1.5 | 0.9 |
| Average Weekly Hours Worked | 0.5 | 1.1 | -1.6 | -0.6 | -0.2 |
| Unit Labor Costs | 2.1 | -1.3 | -2.0 | 2.0 | 2.7 |
| Hourly Compensation | 2.2 | 1.9 | 1.0 | 2.8 | 4.3 |
| Consumer Price Inflation | 3.2 | 1.6 | -0.4 | 3.8 | 2.8 |
| Real Hourly Compensation | -0.9 | 0.3 | 1.4 | -1.0 | 1.4 |
| Non-labor Payments | 3.7 | 7.5 | 0.0 | -0.4 | 3.4 |
| Output per Job | 0.6 | 4.4 | 1.5 | 0.2 | 1.4 |
Source: US Bureau of Labor Statistics http://www.bls.gov/lpc/
Productivity growth can bring about prosperity while productivity regression can jeopardize progress. Cobet and Wilson (2002) provide estimates of output per hour and unit labor costs in national currency and US dollars for the US, Japan and Germany from 1950 to 2000 (see Pelaez and Pelaez, The Global Recession Risk (2007), 137-44). The average yearly rate of productivity change from 1950 to 2000 was 2.9 percent in the US, 6.3 percent for Japan and 4.7 percent for Germany while unit labor costs in USD increased at 2.6 percent in the US, 4.7 percent in Japan and 4.3 percent in Germany. From 1995 to 2000, output per hour increased at the average yearly rate of 4.6 percent in the US, 3.9 percent in Japan and 2.6 percent in Germany while unit labor costs in USD fell at minus 0.7 percent in the US, 4.3 percent in Japan and 7.5 percent in Germany. There was increase in productivity growth in Japan and France within the G7 in the second half of the 1990s but significantly lower than the acceleration of 1.3 percentage points per year in the US. Table II-7 provides average growth rates of indicators in the research of productivity and growth of the US Bureau of Labor Statistics. There is dramatic decline of productivity growth from 2.1 percent per year on average from 1947 to 2017 to 1.2 percent per year on average in the whole cycle from 2007 to 2017. Productivity increased at the average rate of 2.3 percent from 1947 to 2007. There is profound drop in the average rate of output growth from 3.4 percent on average from 1947 to 2017 to 1.6 percent from 2007 to 2017. Output grew at 3.7 percent per year on average from 1947 to 2007. Long-term economic performance in the United States consisted of trend growth of GDP at 3 percent per year and of per capita GDP at 2 percent per year as measured for 1870 to 2010 by Robert E Lucas (2011May). The economy returned to trend growth after adverse events such as wars and recessions. The key characteristic of adversities such as recessions was much higher rates of growth in expansion periods that permitted the economy to recover output, income and employment losses that occurred during the contractions. Over the business cycle, the economy compensated the losses of contractions with higher growth in expansions to maintain trend growth of GDP of 3 percent and of GDP per capita of 2 percent. The US maintained growth at 3.0 percent on average over entire cycles with expansions at higher rates compensating for contractions. US economic growth has been at only 2.2 percent on average in the cyclical expansion in the 35 quarters from IIIQ2009 to IQ2018. 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 second estimate of GDP for IQ2018 (https://www.bea.gov/newsreleases/national/gdp/2018/pdf/gdp1q18_2nd.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/2018/06/stronger-dollar-mediocre-cyclical.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/dollar-appreciation-mediocre-cyclical.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, 3.8 percent from IQ1983 to IQ1991, 3.8 percent from IQ1983 to IIQ1991, 3.8 percent from IQ1983 to IIIQ1991 and at 7.8 percent from IQ1983 to IVQ1983 (https://cmpassocregulationblog.blogspot.com/2018/06/stronger-dollar-mediocre-cyclical.html and earlier https://cmpassocregulationblog.blogspot.com/2018/04/dollar-appreciation-mediocre-cyclical.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 IQ2018 would have accumulated to 35.4 percent. GDP in IQ2018 would be $20,298.9 billion (in constant dollars of 2009) if the US had grown at trend, which is higher by $2919.2 billion than actual $17,379.7 billion. There are about two trillion dollars of GDP less than at trend, explaining the 20.6 million unemployed or underemployed equivalent to actual unemployment/underemployment of 12.1 percent of the effective labor force (https://cmpassocregulationblog.blogspot.com/2018/06/twenty-one-million-unemployed-or.html and earlier https://cmpassocregulationblog.blogspot.com/2018/05/twenty-one-million-unemployed-or.html). US GDP in IQ2018 is 14.4 percent lower than at trend. US GDP grew from $14,991.8 billion in IVQ2007 in constant dollars to $17,379.7 billion in IQ2018 or 15.9 percent at the average annual equivalent rate of 1.5 percent. Professor John H. Cochrane (2014Jul2) estimates US GDP at more than 10 percent below trend. Cochrane (2016May02) measures GDP growth in the US at average 3.5 percent per year from 1950 to 2000 and only at 1.76 percent per year from 2000 to 2015 with only at 2.0 percent annual equivalent in the current expansion. Cochrane (2016May02) proposes drastic changes in regulation and legal obstacles to private economic activity. The US missed the opportunity to grow at higher rates during the expansion and it is difficult to catch up because growth rates in the final periods of expansions tend to decline. The US missed the opportunity for recovery of output and employment always afforded in the first four quarters of expansion from recessions. Zero interest rates and quantitative easing were not required or present in successful cyclical expansions and in secular economic growth at 3.0 percent per year and 2.0 percent per capita as measured by Lucas (2011May). There is cyclical uncommonly slow growth in the US instead of allegations of secular stagnation. There is similar behavior in manufacturing. There is classic research on analyzing deviations of output from trend (see for example Schumpeter 1939, Hicks 1950, Lucas 1975, Sargent and Sims 1977). The long-term trend is growth of manufacturing at average 3.2 percent per year from Apr 1919 to Apr 2018. Growth at 3.2 percent per year would raise the NSA index of manufacturing output from 108.3221 in Dec 2007 to 154.7937 in Apr 2018. The actual index NSA in Apr 2018 is 104.3625, which is 32.6 percent below trend. Manufacturing output grew at average 2.0 percent between Dec 1986 and Apr 2018. Using trend growth of 2.0 percent per year, the index would increase to 135.5768 in Apr 2018. The output of manufacturing at 104.3625 in Apr 2018 is 23.0 percent below trend under this alternative calculation.
Table II-7, US, Productivity and Costs, Average Annual Percentage Changes 2007-2017, 1947-2007 and 1947-2017
| Average Annual Percentage Rate 2007-2017 | Average Annual Percentage Rate 1947-2007 | Average Annual Percentage Rate 1947-2017 | |
| Productivity | 1.2 | 2.3 | 2.1 |
| Output | 1.6 | 3.7 | 3.4 |
| Hours | 0.4 | 1.4 | 1.2 |
| Employment | 0.4 | 1.6 | 1.5 |
| Average Weekly Hours | -0.8* | -14.4* | -15.1* |
| Hourly Compensation | 2.0 | 5.4 | 4.9 |
| Consumer Price Inflation | 1.7 | 3.8 | 3.5 |
| Real Hourly Compensation | 0.3 | 1.7 | 1.5 |
| Unit Labor Costs | 0.8 | 3.0 | 2.7 |
| Unit Non-Labor Payments | 2.1 | 3.5 | 3.3 |
| Output per Job | 1.1 | 2.0 | 1.9 |
* Percentage Change
Source: US Bureau of Labor Statistics http://www.bls.gov/lpc/
Unit labor costs increased sharply during the Great Inflation from the late 1960s to 1981 as shown by sharper slope in Chart II-8. Unit labor costs continued to increase but at a lower rate because of cyclic factors and not because of imaginary secular stagnation.
Chart II-8, US, Nonfarm Business, Unit Labor Costs, 1947-2018, Index 2009=100
Source: US Bureau of Labor Statistics http://www.bls.gov/lpc/
Real hourly compensation increased at relatively high rates after 1947 to the early 1970s but reached a plateau that lasted until the early 1990s, as shown in Chart II-9. There were rapid increases until the global recession. Cyclic factors and not alleged secular stagnation explain the interruption of increases in real hourly compensation.
Chart II-9, US, Nonfarm Business, Real Hourly Compensation, 1947-2018, Index 2009=100
Source: US Bureau of Labor Statistics http://www.bls.gov/lpc/
© Carlos M. Pelaez, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018.
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