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Identifying the roots of inequality of opportunity in South Korea by application of algorithmic approaches

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  • Seungwoo Han

    (The State University of New Jersey)

Abstract

This study identifies the roots of inequality of opportunity in South Korea by applying algorithmic approaches to survey data. In contrast to extant studies, we identify the roots of inequality of opportunity by estimating the importance of variables, interpreting the estimated results, and analyzing the importance of individual variables, instead of measuring inequality of opportunity. We apply a decision tree classification algorithm, light gradient boosting machine, and SHapley Additive exPlanations to estimate the importance of the studied variables and interpret the estimated results. According to the estimated results, the region where the individuals grew up, their gender, and their father’s job during their childhood were the main factors contributing to inequality of opportunity. This study proves that the considerable regional disparity and social environment perpetuate gender inequality in South Korean society. It argues that an individual’s socio-economic achievements are strongly influenced by their father’s background, thus, outweighing other family background-related factors. Individuals receive unequal opportunities owing to a combination of region, father’s background, and their own gender, thereby, affecting their socioeconomic achievements. If these factors remain influential from birth to adulthood, removing the conditions that structure them would be one way to achieve equality of opportunity.

Suggested Citation

  • Seungwoo Han, 2022. "Identifying the roots of inequality of opportunity in South Korea by application of algorithmic approaches," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-10, December.
  • Handle: RePEc:pal:palcom:v:9:y:2022:i:1:d:10.1057_s41599-021-01026-y
    DOI: 10.1057/s41599-021-01026-y
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    3. Oscar Torrealba Rodriguez, 2024. "The weight of circumstances in the inequality of opportunity in Mexico: an estimation over a wide set based on machine learning," Sobre México. Revista de Economía, Sobre México. Temas en economía, vol. 1(9), pages 160-195.

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