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Disentangling the dynamics of social assistance: A linked survey-Register data cohort study of long-term social assistance recipients in Norway.
PLOS ONE ( IF 3.7 ) Pub Date : 2020-03-27 , DOI: 10.1371/journal.pone.0230891
Kristian Heggebø 1 , Espen Dahl 2 , Kjetil A van der Wel 2
Affiliation  

Social assistance is a means-tested benefit that is supposed to be a short-term, temporary economic support. Understanding why some individuals are in repeated or continuous need of social assistance is thus of obvious policy relevance, but the dynamics of social assistance receipt remain poorly understood. In 2005, a survey among long-term recipients of social assistance in Norway collected data on (a) childhood disadvantages, (b) health status, (c) health behaviors, (d) psychological resources, and (e) social ties, in addition to basic sociodemographic information. This rich survey data has been linked with tax register data from 2005–2013, enabling us to explore the detailed characteristics of long-term social assistance recipients who are unable to reach financial self-sufficiency. Results from linear probability models show that surprisingly few of the 28 explanatory variables are statistically associated with social assistance dynamics, with two important exceptions: People with drug problems and immigrants both have a much higher probability of social assistance receipt. Yet overall, it is challenging to ‘predict’ social assistance dynamics, indicating that randomness most likely plays a non-negligible role. The 28 explanatory variables do a far better job in predicting both labor market success (employment), labor market preparation (work assessment allowance), and labor market withdrawal (disability benefit utilization). Thus, there seems to be something distinctive about the processes leading to continued social assistance recipiency, where randomness could be a more influential force.



中文翻译:

弄清社会救助的动态:一项针对挪威长期社会救助接受者的链接调查-注册数据队列研究。

社会救助是一项经过经济状况检验的收益,应该被认为是短期的,暂时的经济支持。因此,了解为什么某些人反复或持续需要社会救助具有明显的政策意义,但是对社会救助收受动态的了解仍然很少。2005年,对挪威的长期社会援助接受者进行了一项调查,收集了以下方面的数据:(a)儿童期的不利条件,(b)健康状况,(c)健康行为,(d)心理资源和(e)社会关系。除了基本的社会人口统计信息。这些丰富的调查数据已与2005-2013年的税务登记数据相关联,使我们能够探索无法实现财务自给自足的长期社会救助接受者的详细特征。线性概率模型的结果表明,出乎意料的是,在28个解释变量中,很少有统计数据与社会援助动态相关,但有两个重要的例外:吸毒者和移民都有较高的社会援助收受概率。然而,总的来说,“预测”社会救助动态具有挑战性,这表明随机性很可能发挥不可忽视的作用。这28个解释变量在预测劳动力市场成功(就业),劳动力市场准备(工作评估津贴)和劳动力市场退出(残疾收益利用)方面都做得更好。因此,在导致社会援助持续接受的过程中似乎存在一些独特之处,其中随机性可能是更具影响力的力量。

更新日期:2020-03-27
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