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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. 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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  12. N. Gregory Mankiw & Ricardo Reis, 2001. "Sticky Information Versus Sticky Prices: A Proposal to Replace the New Keynesian Phillips Curve," NBER Working Papers 8290, National Bureau of Economic Research, Inc.
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Cited by:
  1. 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.
  2. Doz, Catherine & Giannone, Domenico & Reichlin, Lucrezia, 2006. "A quasi maximum likelihood approach for large approximate dynamic factor models," Working Paper Series 0674, European Central Bank.
  3. 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.
  4. 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.
  5. Mackowiak, Bartosz Adam & Moench, Emanuel & Wiederholt, Mirko, 2009. "Sectoral Price Data and Models of Price Setting," CEPR Discussion Papers 7339, C.E.P.R. Discussion Papers.
  6. 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 -.
  7. Michal Brzoza-Brzezina & Jacek Kotlowski, 2009. "Estimating pure inflation in the Polish economy," Working Papers 37, Department of Applied Econometrics, Warsaw School of Economics.
  8. Bai, Jushan & Ng, Serena, 2013. "Principal components estimation and identification of static factors," Journal of Econometrics, Elsevier, vol. 176(1), pages 18-29.
  9. Koopman, Siem Jan & van der Wel, Michel, 2013. "Forecasting the US term structure of interest rates using a macroeconomic smooth dynamic factor model," International Journal of Forecasting, Elsevier, vol. 29(4), pages 676-694.
  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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