Proceedings of the 45th International Academic Conference, London

MINING OF CLASSIFICATION TREES TO ANALYZE A MULTIDIMENSIONAL PHENOMENON

ANA CECILIA PARADA ROJAS, HUMBERTO RÍOS BOLÍVAR, JORGE OMAR RAZO DE ANDA

Abstract:

During periods of remarkable trade openness, increase income inequality in many countries. This paper analyzes how factors that influence inequality due to commercial globalization interact each other. For which a reliable Classifier Tree -selected through a modeling process of bootstrapping- is built, it has 14 knowledge rules and classifies 84% of the observations correctly. This model indicates that inequality‘s changes into a country, due greater economic integration, depend principally on the labor market’ structure –in agricultural countries and urbanization processes (industrialization) it reduces depending in turn on the rule of law; on the other hand, in countries with a strong service sector and good trade terms it increases in periods of stagnation or with low levels of high technology exports.

Keywords: Income Inequality, Globalization, International Trade, Data Mining, Classification and Regression Tree (CART)

DOI: 10.20472/IAC.2019.045.033

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