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Shedding Light on the Doing Business Index: a Machine Learning Approach Cover

Shedding Light on the Doing Business Index: a Machine Learning Approach

Open Access
|Sep 2019

Abstract

Background: The World Bank (WB) acknowledged the importance of business regulatory environment and therefore created a metric which ranks 190 countries based on their level of business regulation for domestic firms measured by the Doing Business Index (DBI).

Objectives: The question which attracted our attention is whether all the observed entities should be given the same weighting scheme.

Methods/Approach: The approach we propose as an answer is two-fold. First, we cluster the countries covered by the DBI. In the next step, we apply the statistical multivariate Composite I-distance Indicator (CIDI) methodology to determine new, data-driven weights for each of the retained clusters.

Results: The obtained results show that there is a difference between the weighting schemes proposed by the CIDI methodology.

Conclusions: One can argue that one weighting scheme does not fit all the observed countries, meaning that additional analyses on the DBI are suggested to explore its stability and its weighting scheme.

DOI: https://doi.org/10.2478/bsrj-2019-019 | Journal eISSN: 1847-9375 | Journal ISSN: 1847-8344
Language: English
Page range: 73 - 84
Submitted on: Apr 20, 2018
Accepted on: Nov 12, 2018
Published on: Sep 16, 2019
Published by: IRENET - Society for Advancing Innovation and Research in Economy
In partnership with: Paradigm Publishing Services
Publication frequency: 2 times per year

© 2019 Milica Maričić, Milica Bulajić, Zoran Radojičić, Veljko Jeremić, published by IRENET - Society for Advancing Innovation and Research in Economy
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.