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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