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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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  • Carlos Carvalho & Niels Arne Dam, 2009. "Estimating the cross-sectional distribution of price stickiness from aggregate data," Staff Reports 419, Federal Reserve Bank of New York.
  • Handle: RePEc:fip:fednsr:419
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    Cited by:

    1. 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.
    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. 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.
    4. 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.

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