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Abstract

A non-parametric efficient statistical method, Random Forests, is implemented for the selection of the determinants of Central Bank Independence (CBI) among a large database of economic, political, and institutional variables for OECD countries. It permits ranking all the determinants based on their importance in respect to the CBI and does not impose a priori assumptions on potential nonlinear relationships in the data. Collinearity issues are resolved, because correlated variables can be simultaneously considered.

DOI

10.22237/jmasm/1553610953

Recommended Citation

Cavicchioli, M., Papana, A., Dagiasis, A. P., & Pistoresi, B. (2018). A random forests approach to assess determinants of central bank independence. Journal of Modern Applied Statistical Methods, 17(2), eP2611. doi: 10.22237/jmasm/1553610953

Response to reviewers_JMASM.docx (23 kB)
Reply to Reviewers

revised_JMASM_CBI_track_changes.docx (108 kB)
revised MS with track changes

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