Poverty Dynamics in Turkey: A Multinomial Logit Model

Senem Çakmak Şahin, İ. Kılıç
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引用次数: 1

Abstract

The availability of longitudinal data allows researchers to analyse the dynamics of poverty. By using the Turkish Statistical Institute’s (TurkStat) Income and Living Conditions Survey micro dataset, we analyse the households’ long-term monetary poverty conditions. We categorise poverty as transitory and chronic and employ the multinomial logit method to analyse determinants of each types of poverty. Results indicate that education and household size are the most effective factors for reducing transitory poverty, and for chronic poverty, the most effective factors are having a regular job and having a skilled occupation; insurance, home ownership, and number of children are important determinants for both types of poverty.
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土耳其的贫困动态:一个多项逻辑模型
纵向数据的可用性使研究人员能够分析贫困的动态。通过使用土耳其统计研究所(TurkStat)的收入和生活条件调查微观数据集,我们分析了家庭的长期货币贫困状况。我们将贫困分为暂时性和慢性,并采用多项逻辑方法来分析每种贫困类型的决定因素。结果表明,教育程度和家庭规模是减少暂时贫困最有效的因素,而对于长期贫困,最有效的因素是拥有固定工作和拥有技术职业;保险、房屋所有权和子女数量是这两种贫困的重要决定因素。
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来源期刊
Ekonomika Vilniaus Universitetas
Ekonomika Vilniaus Universitetas Economics, Econometrics and Finance-Economics, Econometrics and Finance (all)
CiteScore
1.40
自引率
0.00%
发文量
15
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