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  • 标题:A GMM-Based Test for Normal Disturbances of the Heckman Sample Selection Model
  • 本地全文:下载
  • 作者:Pfaffermayr, Michael
  • 期刊名称:Econometrics
  • 印刷版ISSN:2225-1146
  • 出版年度:2014
  • 卷号:2
  • 期号:4
  • 页码:151-168
  • 出版社:MDPI, Open Access Journal
  • 摘要:The Heckman sample selection model relies on the assumption of normal and homoskedastic disturbances. However, before considering more general, alternative semiparametric models that do not need the normality assumption, it seems useful to test this assumption. Following Meijer and Wansbeek (2007), the present contribution derives a GMM-based pseudo-score LM test on whether the third and fourth moments of the disturbances of the outcome equation of the Heckman model conform to those implied by the truncated normal distribution. The test is easy to calculate and in Monte Carlo simulations it shows good performance for sample sizes of 1000 or larger.
  • 关键词:sample selection model; GMM; normality; pseudo-score LM test
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