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Determinants of Central Bank Independence: a Random Forest Approach

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Listed:
  • Maddalena Cavicchioli
  • Angeliki Papana
  • Ariadni Papana Dagiasis
  • Barbara Pistoresi

Abstract

In this paper we implement an efficient non-parametric statistical method, Random survival forests, for the selection of the determinants of Central Bank Independence (CBI) among a large database of political and economic variables for OECD countries. This statistical technique enables us to overcome omitted variables and over omitting problems. It turns out that the economic variables are major determinants compared to the political ones and linear and nonlinear effects of chosen predictors on CBI are found.

Suggested Citation

  • Maddalena Cavicchioli & Angeliki Papana & Ariadni Papana Dagiasis & Barbara Pistoresi, 2016. "Determinants of Central Bank Independence: a Random Forest Approach," Department of Economics 0086, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    • Handle: RePEc:mod:depeco:0086
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    References listed on IDEAS

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    1. Alesina, Alberto & Stella, Andrea, 2010. "The Politics of Monetary Policy," Handbook of Monetary Economics, in: Benjamin M. Friedman & Michael Woodford (ed.), Handbook of Monetary Economics, edition 1, volume 3, chapter 18, pages 1001-1054, Elsevier.
    2. Brumm, Harold J., 2011. "Inflation and central bank independence: Two-way causality?," Economics Letters, Elsevier, vol. 111(3), pages 220-222, June.
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    More about this item

    Keywords

    Central bank independence; political and economic determinants; Random survival forests;
    All these keywords.

    JEL classification:

    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access

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