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Peer Effects in Central Banking

Author

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  • Roman Horvath

    (Charles University)

Abstract

We provide a new explanation for why central banks have become transparent over the last three decades. We apply recently developed social interaction panel regression models for the observational data, which allow the identification of peer effects. The identification is based on variations in the past monetary policy regime exogenously determined with respect to transparency. Previous literature has argued that domestic factors such as macroeconomic stability were behind the trend toward greater transparency. In contrast, our results indicate that transparency primarily increased because of a favorable global environment and, importantly, because of the peer effects among central bankers. Central bankers thus learned from each other’s experiences regarding transparency.

Suggested Citation

  • Roman Horvath, 2020. "Peer Effects in Central Banking," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 68(4), pages 764-814, December.
  • Handle: RePEc:pal:imfecr:v:68:y:2020:i:4:d:10.1057_s41308-020-00121-5
    DOI: 10.1057/s41308-020-00121-5
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    More about this item

    Keywords

    C31; D83; E58;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

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