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Linking Individual and Aggregate Price Changes

Author

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  • Attila Rátfai

    () (Central European University, Budapest)

Abstract

Standard 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.

Suggested Citation

  • Attila Rátfai, 2002. "Linking Individual and Aggregate Price Changes," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 B4-2, International Conferences on Panel Data.
  • Handle: RePEc:cpd:pd2002:b4-2
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    File URL: http://econpapers.repec.org/cpd/2002/72_Ratfai.pdf
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Marcela Eslava & John Haltiwanger & Adriana Kugler & Maurice Kugler, 2010. "Factor Adjustments after Deregulation: Panel Evidence from Colombian Plants," The Review of Economics and Statistics, MIT Press, pages 378-391.
    2. Babutsidze, Zakaria, 2006. "(S,s) Pricing: Does the Heterogeneity Wipe Out the Asymmetry on Micro Level?," MERIT Working Papers 033, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    3. Arpaia, Alfonso & Pérez, Esther & Pichelmann, Karl, 2009. "Understanding labour income share dynamics in Europe," MPRA Paper 15649, University Library of Munich, Germany.
    4. Dhyne, Emmanuel & Fuss, Catherine & Pesaran, M. Hashem & Sevestre, Patrick, 2011. "Lumpy Price Adjustments: A Microeconometric Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(4), pages 529-540.
    5. Emmanuel Dhyne, 2009. "A global assessment of the degree of price stickiness – results from the NBB business survey," Working Paper Research 171, National Bank of Belgium.
    6. Giovanni Caggiano & Efrem Castelnuovo, 2008. "Long Memory and Non-Linearities in International Inflation," "Marco Fanno" Working Papers 0076, Dipartimento di Scienze Economiche "Marco Fanno".

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    Keywords

    Simulated Maximum Likelihood estimation; panel data; inflation dynamics; (S; s) pricing;

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