Sample Selection Model with Bootstrap (BPSSM) Approach:

Please use this identifier to cite or link to this item: http://umt-ir.umt.edu.my:8080/handle/123456789/5488

Title:	Sample Selection Model with Bootstrap (BPSSM) Approach:
Other Titles:	Case Study of the Malaysian Population and Family Survey
Authors:	Muhamad Safiih Lola Wan Saliha Wan Alwi Nurul Hila Zainuddin
Keywords:	Sampel Selection Bootstrap Standard Error Confidence Intervals
Issue Date:	2016
Publisher:	Scientific Research Publishing
Abstract:	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.
URI:	http://hdl.handle.net/123456789/5488
Appears in Collections:	Journal Articles

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