The Prediction of Occupation Using Multiple Logit Models
The Prediction of Occupation Using Multiple Logit Models
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使用多个 Logit 模型预测职业
DOI：
10.2307/2525826
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发表时间：
1975
影响因子：
1.5
通讯作者：
R. Strauss
中科院分区：
文献类型：
--
作者：
P. Schmidt;R. Strauss
按种族和性别对就业模式进行的经济分析通常涉及根据职业的平均受教育程度，为不同职业的有关种族-性别群体构建相对就业份额指数。贝克尔（Becker）和吉尔曼（Gilman）等人使用这种标准化的百分比来分析黑人和妇女获得工作的相对机会，以及分析基于其他特征的工作歧视指数的变化。我们在这里建议通过估计职业成就的多重logit模型来分析就业模式，使用种族，性别，教育程度和劳动力市场经验作为解释变量。这种直接方法的优点是，它不需要对适当的参考点（如职业的平均受教育程度）进行假设，并且分析可以基于个人观察而不是百分比。本文的计划如下：第2节发展了基本模型，并报告了1960年、1967年和1970年的结果。第3节通过考虑可能的区域差异和可能的种族和性别相互作用来扩展模型。第四节总结。附录包含了多重logit模型及其最大似然估计的摘要。
ECONOMIC ANALYSIS OF EMPLOYMENT patterns by race and sex typically has involved construction of indices of relative employment shares for the pertinent race-sex groups in various occupations, given the average level of educational attainment in the occupation. Becker [1] and Gilman [3], among others, have used such normalized percentages to analyze relative access to jobs by blacks and women, as well as to analyze variation in such indices of job discrimination on the basis of other characteristics. We propose here instead to analyze patterns of employment by estimating a multiple logit model of occupational attainment, using race, sex, educational attainment and labor market experience as explanatory variables. The advantages of this direct approach are that it makes it unnecessary to make assumptions about an appropriate reference point (such as average educational attainment in the occupation), and that the analysis may be based on individual observations rather than percentages. The plan of the paper is as follows: Section 2 develops the basic model and reports results for 1960, 1967 and 1970. Section 3 extends the model by considering possible regional difference and possible race and sex interactions. Section 4 concludes. The Appendix contains a summary of the multiple logit model and its maximum likelihood estimation.