Wielomianowa analiza logitowa w badaniach aktywności ekonomicznej ludności wiejskiej

W. Kołodziejczak, F. Wysocki
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Abstract

Multinomial logistic regression can be used to analyse economic activity of population and labour market. Its application enables to decompose labour resources according to selected demographic and socio-economic traits in relation to the degree of change in the state of economic population activity. The aim of the paper is to present the possibilities of using the logit models to assess the chances (risks) and probabilities of changes in the state of economic population activity depending on its selected socio-demographic traits. The flows from employment to unemployment, and to economic inactivity were discussed. The research method and the data were described. An interpretation of selected research results was also presented. Due to the need to follow changes of the state of economic population activity over time, individual raw data from the Labour Force Survey are relevant to build multinomial logit models of the labour market. The possibility of decomposition is limited by the size of the sample, which results from the structure of population under Labour Force Survey and from the length of the analysed period. In practice, a satisfactory model alignment requires a consideration of an analysis period which is at least several years long (and combining the data into a coherent base) along with an aggregation of certain population groups (e.g. all non-agricultural sections of PKD or contiguous age classes). Moreover, correct inference also requires knowledge and experience of a researcher and it should take account of a broad socio-economic context, i.e. quality conditions of the reference system.
多项逻辑回归可以用来分析人口和劳动力市场的经济活动。它的应用使我们能够根据与经济人口活动状况变化程度有关的选定的人口和社会经济特征来分解劳动力资源。本文的目的是提出使用logit模型来评估经济人口活动状态变化的机会(风险)和概率的可能性,这取决于其选定的社会人口特征。讨论了从就业到失业和经济不活跃的流动。介绍了研究方法和数据。还介绍了对选定研究结果的解释。由于需要跟踪经济人口活动状态随时间的变化,来自劳动力调查的单个原始数据与建立劳动力市场的多项逻辑模型相关。分解的可能性受到样本规模的限制,这是由劳动力调查下的人口结构和分析期间的长度决定的。在实践中,一个令人满意的模型对齐需要考虑一个至少长达数年的分析期(并将数据合并到一个连贯的基础中)以及某些人口群体的聚集(例如PKD的所有非农业部分或连续的年龄阶层)。此外,正确的推断还需要研究人员的知识和经验,并应考虑到广泛的社会经济背景,即参考系统的质量条件。
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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