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.
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