Fuzzy Modified Error Terms of Sample Selection Model on Married Women Participation in Labour Force

Heckman sample selection model (1979) has been widely used in theoretical field and applications field. However, this model involves uncertainties and ambiguities. To solve these problems, a new approach on error terms of Heckman sample selection model has been developed that hybrids with fuzzy concept through triangular fuzzy number. Sample selection model was made up of two equations which were participant equation and wage equation. Since there exist uncertainty in both variables and error terms of the model, therefore fuzzy error terms method was applied on the errors to obtain efficient values which were more reliable in a fuzzy environment. This method was repeated twice on the errors of sample selection model to acquire a strong relationship between the variables and errors which explains uncertainty. The data set were obtained from Malaysian Population and Family Survey 1994 (MPFS 1994). Minimum values of error terms indicates that modified fuzzy sample selection model with fuzzy error terms performs much better when uncertainty and fuzziness exist. Thus, in terms of uncertainty it was found out that the proposed method was more efficient because it explains the data as well as the relationship between the variables in the model much better than its counterpart.