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Meta-Analysis of the New Keynesian Phillips Curve

Author

Listed:
  • Katarína Danišková

    (Comenius University, Bratislava)

  • Jarko Fidrmuc

Abstract

The New Keynesian Phillips Curve has become an inherent part of modern monetary policy models. It is derived from micro-founded models with rational expectations, sticky prices, and forward and backward-looking subjects on the market. Having reviewed about 200 studies, we analyze the weight of the forward-looking behavior in the hybrid New Keynesian Phillips Curve by means of meta regression. We show that selected data and method characteristics have significant impact on reported results. Moreover, we find a significant publication bias including publications in top journals, while we document no bias for the most cited studies and the most cited authors.

Suggested Citation

  • Katarína Danišková & Jarko Fidrmuc, 2012. "Meta-Analysis of the New Keynesian Phillips Curve," Working Papers 314, Leibniz Institut für Ost- und Südosteuropaforschung (Institute for East and Southeast European Studies).
    • Handle: RePEc:ost:wpaper:314
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    References listed on IDEAS

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    Cited by:

    1. Petra Valickova & Tomas Havranek & Roman Horvath, 2015. "Financial Development And Economic Growth: A Meta-Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 29(3), pages 506-526, July.
    2. Lukas Ryll & Sebastian Seidens, 2019. "Evaluating the Performance of Machine Learning Algorithms in Financial Market Forecasting: A Comprehensive Survey," Papers 1906.07786, arXiv.org, revised Jul 2019.

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    More about this item

    Keywords

    inflation; New Keynesian Phillips curve; meta-analysis; publication bias;
    All these keywords.

    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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