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Concentration Effects, Spatial Mismatch, or Neighborhood Selection? Exploring Labor Market and Neighborhood Variations in Male Unemployment Risk Using Census Microdata from Great Britain

机译:集中效应,空间不匹配还是邻域选择?利用英国的人口普查微观数据探索男性失业风险中的劳动力市场和邻里差异

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A classification of census enumeration districts has recently been added to the 1991 British Census 2% Sample of Anonymised Records (SAR). Through the use of multilevel modeling techniques, the area classification information on the SAR is used to investigate geographical differences in unemployment. Previous research has indicated that where a person lives can affect their propensity to unemployment. However, the understanding of these relationships are confounded by the reciprocal nature of the relationship between unemployment, housing, and geographical location. This paper examines the relative importance of the individual, the type of neighborhood of residence, and the local labor market in which one lives in explaining variations in unemployment risk. It also examines the role of housing tenure at an individual and contextual level in mediating this relationship. Two competing hypotheses are evaluated. The first is that local concentrations of unemployment are the result of the process of neighborhood selection. The other suggests there are contextual affects on unemployment risk, which may include access to job opportunities and “concentration effects.” The paper concludes that most neighborhood level variation in unemployment is due to housing market effects, particularly neighborhood selection. As well as offering insights into the relationship between unemployment and geographical location, this paper aims to demonstrate methodological innovations in the analysis of census microdata. In particular it shows how area classifications can be used in conjunction with microdata in a multilevel modeling framework, to get a better understanding of the role of individual and contextual factors in social processes.
机译:1991年英国人口普查2%匿名记录样本(SAR)最近添加了人口普查枚举区的分类。通过使用多级建模技术,SAR上的区域分类信息可用于调查失业的地理差异。先前的研究表明,一个人居住的地方会影响他们的失业倾向。但是,对这些关系的理解却因失业,住房和地理位置之间的相互关系而混淆。本文研究了个人的相对重要性,居住区的类型以及人们生活在其中的当地劳动力市场,以解释失业风险的变化。它还从个人和背景两个层面考察了住房使用权在调解这种关系中的作用。对两个相互竞争的假设进行了评估。首先是局部失业集中是社区选择过程的结果。另一个建议对失业风险有上下文影响,其中可能包括获得工作机会和“集中效应”。本文得出的结论是,大多数邻里失业水平的变化是由于住房市场的影响,尤其是邻里选择。除了提供有关失业与地理位置之间关系的见解之外,本文还旨在证明普查微观数据分析中的方法创新。特别是,它显示了如何在多层次建模框架中将区域分类与微数据结合使用,以更好地理解个体和背景因素在社会过程中的作用。

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