FUZZY PARAMETRIC SAMPLE SELECTION MODELS OF MARRIED WOMEN FOR NON-PARTICIPATION BY MLE : CASE STUDY THE MPFS-1994 - Safiih, L. Muhamad; Triana, Yaya Sudarya (MEDIA STATISTIKA, 2011)
Models with sample-selection biases are widely used in various fields of economics such as labour economics (see Maddala, Amemiya, and Mroz). The models are usually estimated by Heckman's two-step estimator. However, Heckman's two-step estimator often performs poorly (see Wales and Woodland, Nelson, Paarsch, and Nawata). The data used in this study originated from the survey was conducted by the National Population and Family Development Board of Malaysia under the Ministry of Women, Family and Community Development of Malaysia, called the Malaysian Population and Family Survey 1994 (MPFS, 1994).  The survey was conducted through a questionnaire, were randomly and specifically for married women. The data set focus on married women which provides information on wages, educational attainment, household composition and other socioeconomic characteristic. The Original sample data based on Mroz (1987), there are 4444 records married women. It is necessary to use the maximum likelihood method to estimate the models in such cases. For solving uncertainty data of  a parametric sample selection model, in this paper needs to consider the models estimation using fuzzy modeling approach, called Fuzzy Parametric Sample Selection Model (FPSSM). Fuzzy Parametric sample selection model (FPSSM) is builds as a hybrid to the  conventional parametric sample selection model. Finally, the result showed, FPSSM by Maximum Likelihood Estimator (MLE) estimates of the mean, Standard Deviation (SD).   Keywords:    Econometrics, Fuzzy Number, Heckman Two-Step Estimator,  Married Women,  MLE, Non-participation, Sample Selection Model.