Linking Individual and Aggregate Price Changes
AbstractStandard macroeconomic forecasting indicators and techniques perform poorly in predicting inflation in the short-run. In contrast, the present paper shows that microeconomic price data placed in an empirical framework rooted in (S,s) pricing theory convey extra information on inflation dynamics. The latent variable model designed to capture the gap between the target and the actual price is applied to a unique, highly disaggregated panel data set of consumer prices. Fluctuations in the shape of the cross-sectional density of price deviations contribute to short-run in-sample inflation. Asymmetry in the density particularly matters.
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Bibliographic InfoPaper provided by International Conferences on Panel Data in its series 10th International Conference on Panel Data, Berlin, July 5-6, 2002 with number B4-2.
Date of creation: Mar 2002
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Simulated Maximum Likelihood estimation; panel data; inflation dynamics; (S; s) pricing;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2002-07-04 (All new papers)
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- Emmanuel Dhyne & Catherine Fuss & M. Hashem Pesaran & Patrick Sevestre, 2007.
"Lumpy Price Adjustments: A Microeconometric Analysis,"
CESifo Working Paper Series
2010, CESifo Group Munich.
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- Emmanuel Dhyne, 2009.
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- Giovanni Caggiano & Efrem Castelnuovo, 2008. "Long Memory and Non-Linearities in International Inflation," "Marco Fanno" Working Papers 0076, Dipartimento di Scienze Economiche "Marco Fanno".
- Emmanuel Dhyne & Jerzy Konieczny & Fabio Rumler & Patrick Sevestre, 2009. "Price rigidity in the euro area - An assessment," European Economy - Economic Papers 380, Directorate General Economic and Monetary Affairs (DG ECFIN), European Commission.
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