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  • 标题:Robust Standard Error Estimators for Panel Models: A Unifying Approach
  • 本地全文:下载
  • 作者:Giovanni Millo
  • 期刊名称:Journal of Statistical Software
  • 印刷版ISSN:1548-7660
  • 电子版ISSN:1548-7660
  • 出版年度:2017
  • 卷号:82
  • 期号:1
  • 页码:1-27
  • DOI:10.18637/jss.v082.i03
  • 语种:English
  • 出版社:University of California, Los Angeles
  • 摘要:The different robust estimators for the standard errors of panel models used in applied econometric practice can all be written and computed as combinations of the same simple building blocks. A framework based on high-level wrapper functions for most common usage and basic computational elements to be combined at will, coupling user-friendliness with flexibility, is integrated in the plm package for panel data econometrics in R. Statistical motivation and computational approach are reviewed, and applied examples are provided.
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