What Affects Debt Enforcement Proceedings? Evidence from the Czech Republic

IF 0.4 Q4 ECONOMICS
Daniel Pakši, M. Šimek, Jakub Vontroba
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Abstract

Abstract This paper aims to identify the factors contributing to the unusually high prevalence of over-indebtedness and debt enforcement proceedings in the Czech Republic at the granular geographic level of extended-powers municipalities (ORP). The main reason for this level is simple, not to lose information about differences among the municipalities, since there is quite a sharp contrast even within the same regions. The dependent variable is the share of people with one or more debt enforcement proceedings outstanding against them. We employ a set of explanatory variables including long-term unemployment, socially excluded localities, regional GDP per capita, education level, and a proxy for distance to the local economic center. The results are estimated using panel data regression with random effects, due to the time-invariant nature of certain variables. Because of poor data availability for some variables at this highly localized level, we make several assumptions; for example, we transfer the regional GDP per capita values to all ORPs in the region. Similar problems arise with education level, where we use data from the 2011 national census. Even with these data restrictions, our set of explanatory variables is shown to be statistically significant with the expected coefficient signs. GDP per capita and higher education level have a negative impact on the prevalence of debt enforcement proceedings, while long-term unemployment, the number of socially excluded localities in the area, and the distance-to-center proxy have a positive effect.
什么影响强制执行债务程序?来自捷克共和国的证据
摘要本文旨在确定导致捷克共和国过度负债和债务执法程序异常普遍的因素,这些因素在扩展权力市政当局(ORP)的颗粒地理水平上。设置这一等级的主要原因很简单,即不遗漏有关各城市之间差异的信息,因为即使在同一区域内也存在相当明显的对比。因变量是面临一项或多项债务强制执行程序的人所占比例。我们采用了一系列解释变量,包括长期失业、社会排斥地区、地区人均GDP、教育水平以及与当地经济中心的距离。由于某些变量的时不变性质,使用随机效应的面板数据回归估计结果。由于在这个高度局部化的水平上,一些变量的数据可用性很差,我们做了几个假设;例如,我们将该地区的人均GDP值转移到该地区的所有orp。类似的问题也出现在教育水平上,我们使用了2011年全国人口普查的数据。即使有这些数据限制,我们的解释变量集也显示出具有预期系数符号的统计显著性。人均GDP和高等教育水平对债务执行程序的普遍性有负面影响,而长期失业、该地区被社会排斥的地方数量和到中心的距离代理有积极影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.40
自引率
0.00%
发文量
10
审稿时长
38 weeks
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