Reconstruction of World Bank’s classification of countries

Abstract

This paper’s objective is to analyze whether the classification of countries provided by the World Bank (WB) can be reconstructed with a linear and/or integer-programming model known as multi-group hierarchical discrimination, using only data published by the WB. The WB has a public database containing countries’ economic-financial and political criteria. The model’s parameters were determined for a collection of 44 countries, and the model was verified using another 39 countries. Only four out of 39 countries were misclassified, which shows the elaborated model’s power. Logical analysis of data (LAD) also analyzed the problem. The attempt to reconstruct the classification uses 19 criteria. An important result from the reconstruction is that the methods select the most important criteria. Interestingly, the result proves that the WB classification is not based only on Gross national income (GNI) per capita. The more important criteria (criteria) are Gross domestic product (GDP) growth (annual %), GNI per capita (PPP, current international US dollar), gross capital formation (% of GDP), inflation (GDP deflator, annual %), mobile cellular subscriptions (per 100 people), population growth (annual %), military expenditure (annual %), and fertility rate (total birth per woman). Key words: Multi-group hierarchical discrimination, logical analysis of data, gross national income, country classification.