Maximum Likelihood Estimation for the Generalized Pareto Distribution and Goodness-of-Fit Test with Censored Data

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.

The influence of financial market development on de jure central bank independence in the Asia–Pacific

“…Hence, although trade openness could reduce the CBI, as D'Amato et al (2009) suggested, it is not statistically important in explaining the degree of CBI in the Asia-Pacific countries examined in this paper. The income level represented by the real income per capita level has been statistically significant in lowering the CBI of the sample, supporting the empirical results of Dincer and Eichengreen (2014) and the theoretical assumptions of Cavicchioli et al (2019) andD'Amato et al (2009) mentioned above. Additionally, the lagged inflation has a negative sign and is statistically insignificant in all models.…”

“…(2009) suggested, it is not statistically important in explaining the degree of CBI in the Asia–Pacific countries examined in this paper. The income level represented by the real income per capita level has been statistically significant in lowering the CBI of the sample, supporting the empirical results of Dincer and Eichengreen (2014) and the theoretical assumptions of Cavicchioli et al. (2019) and D'Amato et al.…”

“…Another variable is the real GDP per capita, which accounts for the influence of economic development on the CBI. According to Cavicchioli et al. (2019), a higher real GDP reduces a CB's incentive to implement an inflationary monetary policy, causing a higher CBI.…”

“…Another variable is the real GDP per capita, which accounts for the influence of economic development on the CBI. According to Cavicchioli et al (2019), a higher real GDP reduces a CB's incentive to implement an inflationary monetary policy, causing a higher CBI. Nonetheless, the effect could be the opposite, as citizens in high-income countries could accept higher inflation due to better inflation hedging.…”

“…Agur (2019) focused on the role of institutional quality in deciding CBI using the fixed effect panel estimation; better institutional quality relates to a greater CBI. Lastly, Cavicchioli et al (2019) deployed the random forest method on data from OCED countries. They found that income, inflation and the business cycle are significant factors behind the CBI.…”