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  • 标题:Sample Selection Model with Bootstrap (BPSSM) Approach: Case Study of the Malaysian Population and Family Survey
  • 本地全文:下载
  • 作者:Muhamad Safiih Lola ; Wan Saliha Wan Alwi ; Nurul Hila Zainuddin
  • 期刊名称:Open Journal of Statistics
  • 印刷版ISSN:2161-718X
  • 电子版ISSN:2161-7198
  • 出版年度:2016
  • 卷号:06
  • 期号:05
  • 页码:741-748
  • DOI:10.4236/ojs.2016.65060
  • 语种:English
  • 出版社:Scientific Research Publishing
  • 摘要:Heckman Sampel Selection Model (PSSM) has been adopted widely in the study of labour work. This model contains exogenous, endogenous and standard error variables. However, this model is constantly exposed to high inaccuracy of estimation result. Therefore, to obtain an accurate and precise estimation, the bootstrap approach is introduced. The bootstrap approach will be hybrid with PSSM model known as BPSSM to achieve estimation result that is more precise. Then, the BPSSM is applied to Malaysian Population and Family Survey 1994 (MPFS-1994) data. The results showed that BPSSM provide a smaller standard error and shorter confidence intervals.
  • 关键词:Sampel Selection;Bootstrap;Standard Error;Confidence Intervals
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