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Estimating the cross-sectional distribution of price stickiness from aggregate data

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  • Carlos Carvalho
  • Niels Arne Dam

Abstract

We estimate a multisector sticky-price model for the U.S. economy in which the degree of price stickiness is allowed to vary across sectors. For this purpose, we use a specification that allows us to extract information about the underlying cross-sectional distribution from aggregate data. Identification is possible because sectors play different roles in determining the response of aggregate variables to shocks at different frequencies: Sectors where prices are stickier are relatively more important in determining the low-frequency response. Estimating the model using only aggregate data on nominal and real output, we find that the inferred distribution of price stickiness is strikingly similar to the empirical distribution constructed from the recent microeconomic evidence on price setting in the U.S. economy. We also provide macro-based estimates of the underlying distribution for ten other countries. Finally, we explore our Bayesian approach to combine the aggregate time-series data with the microeconomic information on the distribution of price rigidity. Our results show that allowing for this type of heterogeneity is critically important to understanding the joint dynamics of output and prices, and it constitutes a step toward reconciling the extent of nominal price rigidity implied by aggregate data with the evidence from microeconomic data on price stickiness.

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Bibliographic Info

Paper provided by Federal Reserve Bank of New York in its series Staff Reports with number 419.

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Date of creation: 2009
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Handle: RePEc:fip:fednsr:419

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Keywords: Prices ; Bayesian statistical decision theory ; Time-series analysis;

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References

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  1. Dixon, Huw & Kara, Engin, 2005. "Persistence and nominal inertia in a generalized Taylor economy: how longer contracts dominate shorter contracts," Working Paper Series 0489, European Central Bank.
  2. Carlos Carvalho & Fernanda Nechio, 2011. "Aggregation and the PPP Puzzle in a Sticky-Price Model," American Economic Review, American Economic Association, vol. 101(6), pages 2391-2424, October.
  3. Coenen, Gunter & Levin, Andrew T. & Christoffel, Kai, 2007. "Identifying the influences of nominal and real rigidities in aggregate price-setting behavior," Journal of Monetary Economics, Elsevier, vol. 54(8), pages 2439-2466, November.
  4. Ball, Laurence & Romer, David, 1990. "Real Rigidities and the Non-neutrality of Money," Review of Economic Studies, Wiley Blackwell, vol. 57(2), pages 183-203, April.
  5. Kevin D. Sheedy, 2007. "Inflation persistence when price stickiness differs between industries," LSE Research Online Documents on Economics 3738, London School of Economics and Political Science, LSE Library.
  6. Argia M. Sbordone, 2001. "Prices and Unit Labor Costs: A New Test of Price Stickiness," Departmental Working Papers 199822, Rutgers University, Department of Economics.
  7. Sims, Christopher A, 2002. "Solving Linear Rational Expectations Models," Computational Economics, Society for Computational Economics, vol. 20(1-2), pages 1-20, October.
  8. Etienne Gagnon, 2007. "Price setting during low and high inflation: evidence from Mexico," International Finance Discussion Papers 896, Board of Governors of the Federal Reserve System (U.S.).
  9. Taylor, John B, 1979. "Staggered Wage Setting in a Macro Model," American Economic Review, American Economic Association, vol. 69(2), pages 108-13, May.
  10. Carvalho Carlos, 2006. "Heterogeneity in Price Stickiness and the Real Effects of Monetary Shocks," The B.E. Journal of Macroeconomics, De Gruyter, vol. 6(3), pages 1-58, December.
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Cited by:
  1. Fang Yao, 2010. "Aggregate Hazard Function in Price-Setting: A Bayesian Analysis Using Macro Data," SFB 649 Discussion Papers SFB649DP2010-020, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  2. Bouakez, Hafedh & Cardia, Emanuela & Ruge-Murcia, Francisco, 2014. "Sectoral price rigidity and aggregate dynamics," European Economic Review, Elsevier, vol. 65(C), pages 1-22.
  3. Huw Dixon & Engin Kara, 2011. "Taking Multi-Sector Dynamic General Equilibrium Models to the Data," Koç University-TUSIAD Economic Research Forum Working Papers 1125, Koc University-TUSIAD Economic Research Forum.
  4. Stefano Eusepi & Bart Hobijn & Andrea Tambalotti, 2011. "CONDI: A Cost-of-Nominal-Distortions Index," American Economic Journal: Macroeconomics, American Economic Association, vol. 3(3), pages 53-91, July.

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