TITLE:
Sample Selection Model with Bootstrap (BPSSM) Approach: 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
JOURNAL NAME:
Open Journal of Statistics,
Vol.6 No.5,
September
22,
2016
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.