Sample Selection Model with Bootstrap (BPSSM) Approach:

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dc.contributor.authorMuhamad Safiih Lola
dc.contributor.authorWan Saliha Wan Alwi
dc.contributor.authorNurul Hila Zainuddin
dc.date.accessioned2017-04-09T08:42:09Z
dc.date.available2017-04-09T08:42:09Z
dc.date.issued2016
dc.description.abstractHeckman 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.en_US
dc.identifier.urihttp://hdl.handle.net/123456789/5488
dc.language.isoenen_US
dc.publisherScientific Research Publishingen_US
dc.subjectSampel Selectionen_US
dc.subjectBootstrapen_US
dc.subjectStandard Erroren_US
dc.subjectConfidence Intervalsen_US
dc.titleSample Selection Model with Bootstrap (BPSSM) Approach:en_US
dc.title.alternativeCase Study of the Malaysian Population and Family Surveyen_US
dc.typeArticleen_US
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