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

Cavicchioli, M., A., Papana, A., Papana Diagasis e B., Pistoresi. "Determinants of Central Bank independence: a random forest approach" Working paper, DEMB WORKING PAPER SERIES, Dipartimento di Economia Marco Biagi - Università di Modena e Reggio Emilia, 2016. https://doi.org/10.25431/11380_1101348

Determinants of Central Bank independence: a random forest approach

Cavicchioli, M.;Pistoresi, B.
2016

Abstract

In this paper we implement an effcient non-parametric statistical method, Random survival forests, for the selection of the determinants of Central Bank Independence (CBI) among a large data base of political and economic variables for OECD countries.This statistical technique enables us to overcome omitted variables and overftting problems. It turns out that the economic variables are major determinants compared to the political ones and linear andnonlinear effects of chosen predictors on CBI are found.
Maggio
Cavicchioli, M.; Papana, A.; Papana Diagasis, A.; Pistoresi, B.
Cavicchioli, M., A., Papana, A., Papana Diagasis e B., Pistoresi. "Determinants of Central Bank independence: a random forest approach" Working paper, DEMB WORKING PAPER SERIES, Dipartimento di Economia Marco Biagi - Università di Modena e Reggio Emilia, 2016. https://doi.org/10.25431/11380_1101348
File in questo prodotto:
File Dimensione Formato  
0086.pdf

accesso aperto

Tipologia: Versione dell'editore (versione pubblicata)
Dimensione 447.06 kB
Formato Adobe PDF
447.06 kB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

Caricamento pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1101348
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact