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Relative Goods' Prices, Pure Inflation, and the Phillips Correlation

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  • Ricardo Reis
  • Mark W. Watson

Abstract

This paper uses a dynamic factor model for the quarterly changes in consumption goods’ prices to separate them into three independent components: idiosyncratic relative-price changes, a low-dimensional index of aggregate relative-price changes, and an index of equiproportional changes in all inflation rates, that we label “pure” inflation. The paper estimates the model on U.S. data since 1959, and it presents a simple structural model that relates the three components of price changes to fundamental economic shocks. We use the estimates of the pure inflation and aggregate relative-price components to answer two questions. First, what share of the variability of inflation is associated with each component, and how are they related to conventional measures of monetary policy and relative-price shocks? We find that pure inflation accounts for 15-20% of the variability in inflation while our aggregate relative-price index accounts most of the rest. Conventional measures of relative prices are strongly but far from perfectly correlated with our relative-price index; pure inflation is only weakly correlated with money growth rates, but more strongly correlated with nominal interest rates. Second, what drives the Phillips correlation between inflation and measures of real activity? We find that the Phillips correlation essentially disappears once we control for goods’ relative-price changes. This supports modern theories of inflation dynamics based on price rigidities and many consumption goods.

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Bibliographic Info

Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 13615.

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Date of creation: Nov 2007
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Publication status: published as Ricardo Reis & Mark W. Watson, 2010. "Relative Goods' Prices, Pure Inflation, and the Phillips Correlation," American Economic Journal: Macroeconomics, American Economic Association, vol. 2(3), pages 128-57, July.
Handle: RePEc:nbr:nberwo:13615

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  1. N. Gregory Mankiw & Ricardo Reis, 2001. "Sticky Information Versus Sticky Prices: A Proposal to Replace the New Keynesian Phillips Curve," Harvard Institute of Economic Research Working Papers 1922, Harvard - Institute of Economic Research.
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  4. Ben Bernanke & Jean Boivin & Piotr S. Eliasz, 2005. "Measuring the Effects of Monetary Policy: A Factor-augmented Vector Autoregressive (FAVAR) Approach," The Quarterly Journal of Economics, MIT Press, vol. 120(1), pages 387-422, January.
  5. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
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  7. Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2012. "A Quasi–Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1014-1024, November.
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  11. Amengual, Dante & Watson, Mark W., 2007. "Consistent Estimation of the Number of Dynamic Factors in a Large N and T Panel," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 91-96, January.
  12. Hallin, Marc & Liska, Roman, 2007. "Determining the Number of Factors in the General Dynamic Factor Model," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 603-617, June.
  13. Cristadoro, Riccardo & Forni, Mario & Reichlin, Lucrezia & Veronese, Giovanni, 2001. "A Core Inflation Index for the Euro Area," CEPR Discussion Papers 3097, C.E.P.R. Discussion Papers.
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  15. Milton Friedman & Anna J. Schwartz, 1963. "A Monetary History of the United States, 1867-1960," NBER Books, National Bureau of Economic Research, Inc, number frie63-1, October.
  16. Watson, Mark W., 1989. "Recursive solution methods for dynamic linear rational expectations models," Journal of Econometrics, Elsevier, vol. 41(1), pages 65-89, May.
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Cited by:
  1. Doz, Catherine & Giannone, Domenico & Reichlin, Lucrezia, 2006. "A Quasi Maximum Likelihood Approach for Large Approximate Dynamic Factor Models," CEPR Discussion Papers 5724, C.E.P.R. Discussion Papers.
  2. Bai, Jushan & Ng, Serena, 2013. "Principal components estimation and identification of static factors," Journal of Econometrics, Elsevier, vol. 176(1), pages 18-29.
  3. Siem Jan Koopman & Michel van der Wel, 2011. "Forecasting the U.S. Term Structure of Interest Rates using a Macroeconomic Smooth Dynamic Factor Model," Tinbergen Institute Discussion Papers 11-063/4, Tinbergen Institute.
  4. Tomás Castagnino & Laura D’Amato, 2008. "Regime and Underlying Inflation Dynamics: ¿Generalized Comovement or Relative Price Adjustment?," Ensayos Económicos, Central Bank of Argentina, Economic Research Department, vol. 1(52), pages 87-120, October -.
  5. Gregor W. Smith, 2009. "The Missing Links: Better Measures of Inflation and Inflation Expectations in Canada," C.D. Howe Institute Commentary, C.D. Howe Institute, issue 287, April.
  6. Michal Brzoza-Brzezina & Jacek Kotlowski, 2009. "Estimating pure inflation in the Polish economy," Working Papers 37, Department of Applied Econometrics, Warsaw School of Economics.
  7. Mirko Wiederholt & Emanuel Moench & Bartosz Maćkowiak, 2009. "Sectoral Price Data and Models of Price Setting," 2009 Meeting Papers 666, Society for Economic Dynamics.
  8. Choi, Chi-Young & O'Sullivan, Róisín, 2013. "Heterogeneous response of disaggregate inflation to monetary policy regime change: The role of price stickiness," Journal of Economic Dynamics and Control, Elsevier, vol. 37(9), pages 1814-1832.
  9. Mikael Khan & Louis Morel & Patrick Sabourin, 2013. "The Common Component of CPI: An Alternative Measure of Underlying Inflation for Canada," Working Papers 13-35, Bank of Canada.
  10. Alan K. Detmeister, 2011. "The usefulness of core PCE inflation measures," Finance and Economics Discussion Series 2011-56, Board of Governors of the Federal Reserve System (U.S.).
  11. Kitov, Ivan & Kitov, Oleg, 2012. "Sustainable trends and periodicity in consumer price indices indicate that the era of low energy prices is approaching," MPRA Paper 43392, University Library of Munich, Germany.

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