To Do or Not To Do Business with a Country: A Robust Classification Approach

Journal of Data Science

article

Kuntal Bhattacharyya¹  Pratim Datta² 

[1] Indiana State University;Kent State University

关键词: Global supply chain;    outlier management;    country risk;   

DOI  :  10.6339/JDS.201110_09(4).0008

学科分类：土木及结构工程学

来源: JDS

【 摘 要 】

In the face of global uncertainty and a growing reliance on third party indices to gain a snapshot of a country’s operations, accurate decision making makes or breaks relationships in global trade. Under this aegis, we question the validity of traditional logistic regression using the maximum likelihood estimator (MLE) in classifying countries for doing business. This paper proposes that a weighted version of the Bianco and Yohai (BY) estimator is a superlative and robust (outlier resistant) tool in the hands of practitioners to gauge the correct antecedents of a country’s internal environment and decide whether to do or not do business with that country. In addition, this robust process is effective in differentiating between “problem” countries and “safe” countries for doing business. An existing “R” program for the BY estimation technique by Croux and Haesbroeck has been modified to fit our cause.

【 授权许可】

CC BY