MINING OF CLASSIFICATION TREES TO ANALYZE A MULTIDIMENSIONAL PHENOMENON

Ana Cecilia Parada Rojas (), Humberto Ríos Bolívar () and Jorge Omar Razo de Anda ()
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Ana Cecilia Parada Rojas: Instituto Politécnico Nacional
Humberto Ríos Bolívar: Instituto Politécnico Nacional
Jorge Omar Razo de Anda: Instituto Politécnico Nacional

No 9010809, Proceedings of International Academic Conferences from International Institute of Social and Economic Sciences

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) (search for similar items in EconPapers)
JEL-codes: C44 D33 F10 (search for similar items in EconPapers)
Pages: 21 pages
Date: 2019-06
New Economics Papers: this item is included in nep-int
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Published in Proceedings of the Proceedings of the 45th International Academic Conference, London, Jun 2019, pages 202-222

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Persistent link: https://EconPapers.repec.org/RePEc:sek:iacpro:9010809

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