• Title/Summary/Keyword: Inter-generation Inequality

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A Comparison of Adolescents Internet Use and Learning Conduct Based on their Parents Socio-Economic Status : Focused on Korean Time Use Survey of 2014 (부모의 사회경제적 지위에 따른 청소년들의 인터넷 이용 및 학습 행태 비교: 2014년 생활시간조사자료 분석을 중심으로)

  • Kang Sun-Kyung;Choi Yoon
    • Studies on Life and Culture
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    • v.48
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    • pp.335-374
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    • 2018
  • This study explores the influence of parents socio-economic status on their adolescent children s internet use and learning conduct based on Korean Time Use Survey of 2014, under the assumption that parents socio-economic status can function as a mechanism for reproducing inter-generational inequality due to the difference of their children s internet use and learning conduct. Upon reviewing the weekdays average hours of using internet per day for the students from the age 13, the first year of a middle school to the age 18, the third year of a high school, they spend 15 minutes for information search, and 54 minutes for computer or mobile games. They tend to spend 211 minutes for study in the school, 56 minutes for after school study, and 88 minutes for self-study. According to Tobit regression analysis, the higher the students parents socio-economic status, the bigger the total hour for self-study and after school study. On the other hand, the lower the parents socio-economic status, the bigger the total hour for their adolescents internet or mobile game. The research shows that the lower the parents socio-economic status, the bigger the risk of their adolescent children s exposure to the addiction of the internet and mobile game. This implies that the parents socio-economic status can function to reproduce the inter-generational inequality. Based on the analysis result, this study discusses the practical and policy level implications in social welfare for improving the inequality reproducing mechanism.

Income Inequality Decomposed by Age, Period and Cohort Effects: A Comparison of the Capital and Non-Capital Regions (연령, 시간, 코호트효과를 고려한 소득 불평등: 수도권과 비수도권 간 비교)

  • Jeong, Jun Ho
    • Journal of the Economic Geographical Society of Korea
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    • v.23 no.2
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    • pp.166-181
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    • 2020
  • This paper attempts to compare and analyze the intensity, trend, and regional gap of income inequality, capitalizing upon the Age-Period-Cohort model which considers age, time and cohort effects, with the 1998-2018 Korea Labor Panel (KLIPS) survey data for respondents living in the Capital and Non-Capital Regions. The main analysis results are as follows. First, in the case of both cohort and age effects, those in their 50~60s, including the so-called baby boomers and '386 generation' living in the Capital Region, have relatively lower income inequality effect compared to that of other age groups and cohorts in the Non-Capital Region. Second, the micro-individual characteristics cannot be ignored to account for a regional gap in income inequality, but rather the effects of structural and institutional omitted variables and the social discrimination effects of individual characteristics variables are more significant in explaining it. Overall, intra-and inter-cohort income inequalities appear to overlap.

Optimal Base Station Clustering for a Mobile Communication Network Design

  • Hong, Jung-Man;Lee, Jong-Hyup;Lee, Soong-Hee
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.5 no.5
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    • pp.1069-1084
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    • 2011
  • This paper considers an optimal base station clustering problem for designing a mobile (wireless) communication network. For a given network with a set of nodes (base stations), the problem is to optimally partition the set of nodes into subsets (each called a cluster) such that the associated inter-cluster traffic is minimized under certain topological constraints and cluster capacity constraints. In the problem analysis, the problem is formulated as an integer programming problem. The integer programming problem is then transformed into a binary integer programming problem, for which the associated linear programming relaxation is solved in a column generation approach assisted by a branch-and-bound procedure. For the column generation, both a heuristic algorithm and a valid inequality approach are exploited. Various numerical examples are solved to evaluate the effectiveness of the LP (Linear Programming) based branch-and-bound algorithm.