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On the importance of sectoral shocks for price-setting

  • Beck, Guenter W.
  • Hubrich, Kirstin
  • Marcellino, Massimiliano

We use a novel disaggregate sectoral euro area dataset with a regional breakdown that allows explicit estimation of the sectoral component of price changes (rather than interpreting the idiosyncratic component as sectoral as done in other papers). Employing a new method to extract factors from over-lapping data blocks, we find for our euro area data set that the sectoral component explains much less of the variation in sectoral regional inflation rates and exhibits much less volatility than previous findings for the US indicate. Country- and region-specific factors play an important role in addition to the sector-specific factors. We conclude that sectoral price changes have a 'geographical' dimension, as yet unexplored in the literature, that might lead to new insights regarding the properties of sectoral price changes.

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Paper provided by Center for Financial Studies (CFS) in its series CFS Working Paper Series with number 2009/32.

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Date of creation: 2009
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Handle: RePEc:zbw:cfswop:200932
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  1. N. Gregory Mankiw & Ricardo Reis, 2002. "Sticky Information Versus Sticky Prices: A Proposal To Replace The New Keynesian Phillips Curve," The Quarterly Journal of Economics, MIT Press, vol. 117(4), pages 1295-1328, November.
  2. Mackowiak, Bartosz Adam & Wiederholt, Mirko, 2007. "Optimal Sticky Prices under Rational Inattention," CEPR Discussion Papers 6243, C.E.P.R. Discussion Papers.
  3. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-62, April.
  4. Mirko Wiederholt & Emanuel Moench & Bartosz Maćkowiak, 2009. "Sectoral Price Data and Models of Price Setting," 2009 Meeting Papers 666, Society for Economic Dynamics.
  5. Luis J. Álvarez & Emmanuel Dhyne & Marco Hoeberichts & Claudia Kwapil & Hervé Le Bihan & Patrick Lünnemann & Fernando Martins & Roberto Sabbatini & Harald Stahl & Philip Vermeulen & Jouko Vilmunen, 2006. "Sticky Prices in the Euro Area: A Summary of New Micro-Evidence," Journal of the European Economic Association, MIT Press, vol. 4(2-3), pages 575-584, 04-05.
  6. Emanuel Moench & Serena Ng & Simon Potter, 2009. "Dynamic hierarchical factor models," Staff Reports 412, Federal Reserve Bank of New York.
  7. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2004. "Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach," NBER Working Papers 10220, National Bureau of Economic Research, Inc.
  8. Kapetanios, George & Marcellino, Massimiliano, 2010. "Factor-GMM estimation with large sets of possibly weak instruments," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2655-2675, November.
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  11. Jean Imbs & Haroon Mumtaz & Morten O. Ravn & Helene Rey, 2003. "PPP Strikes Back: Aggregation and the Real Exchange Rate," IEHAS Discussion Papers 0307, Institute of Economics, Centre for Economic and Regional Studies, Hungarian Academy of Sciences.
  12. Massimiliano Marcellino & Carlo A. Favero & Francesca Neglia, 2005. "Principal components at work: the empirical analysis of monetary policy with large data sets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(5), pages 603-620.
  13. Beck, Günter W. & Hubrich, Kirstin & Marcellino, Massimiliano, 2006. "Regional inflation dynamics within and across euro area countries and a comparison with the US," Working Paper Series 0681, European Central Bank.
  14. repec:nbr:nberwo:131477 is not listed on IDEAS
  15. Calvo, Guillermo A., 1983. "Staggered prices in a utility-maximizing framework," Journal of Monetary Economics, Elsevier, vol. 12(3), pages 383-398, September.
  16. 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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