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An Estimation of Sectoral Price Stickiness using Aggregate Data

Author

Listed:
  • Cheng-qi Hou

    (School of Economics and Management, Wuhan University, Wuhan, 430072, China.)

  • Pin Wang

    (School of Finance, Zhongnan University of Economics and Law, Wuhan, 430073, China.)

Abstract
This article studies how to employ aggregate data to estimate sectoral price stickiness, which is described by the Calvo-style price setting. We find that sectoral price stickiness cannot be effectively estimated by the Bayesian approach of the multisector new Keynesian model that is used in Carvalho and Dam (2010). Then, we propose a structural GMM estimation of sectoral new Keynesian Phillips curves to obtain sectoral price stickiness and the results are well consistent with the available microeconomic evidence on price setting.

Suggested Citation

  • Cheng-qi Hou & Pin Wang, 2014. "An Estimation of Sectoral Price Stickiness using Aggregate Data," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 53-70, June.
    • Handle: RePEc:rjr:romjef:v::y:2014:i:2:p:53-70
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    sectoral price stickiness; sectoral new Keynesian Phillips curve; aggregate data; GMM; Bayesian approach;
    All these keywords.

    JEL classification:

    • E12 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Keynes; Keynesian; Post-Keynesian; Modern Monetary Theory
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation

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