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  • 标题:A Bayesian Analysis of Female Wage Dynamics Using Markov Chain Clustering
  • 本地全文:下载
  • 作者:Christoph Pamminger ; Regina Tüchler
  • 期刊名称:Austrian Journal of Statistics
  • 出版年度:2011
  • 卷号:40
  • 期号:04
  • 出版社:Austrian Statistical Society
  • 摘要:

    In this work, we analyze wage careers of women in Austria. We
    identify groups of female employees with similar patterns in their earnings
    development. Covariates such as e.g. the age of entry, the number of children
    or maternity leave help to detect these groups. We find three different types
    of female employees: (1) “high-wage mums”, women with high income and
    one or two children, (2) “low-wage mums”, women with low income and
    ‘many’ children and (3) “childless careers”, women who climb up the career
    ladder and do not have children.
    We use a Markov chain clustering approach to find groups in the discretevalued
    time series of income states. Additional covariates are included when
    modeling group membership via a multinomial logit model.

  • 关键词:Income Career; Transition Data; Multinomial Logit; Auxiliary Mixture Sampler, Markov Chain Monte Carlo
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