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An important progress within the last decade in the development of the selectivity model approach to overcome the inconsistent results if the distributi onal assumptions of the errors terms are made this problem is through the use of semi-parametric method. However, the uncertainties and ambiguities exist in the mod els, particularly the relationship between the endogenou s and exogenous variables. A new framework of the relationship between the endogenous and exogenous variables of semi-parametric sample selection model using the concept of fuzzy modelling is introduced. Through this approach, a flexible fuzzy concept hy brid with the semi-parametric sample selection models known as Fuzzy Semi-Parametric Sample Selection Model (FSPSSM). The elements of vagueness and uncertainty in the models are represented in the model construction, as a way of increasing the available information to produce a more accurate model. This led to the development of the convergence theorem presented in the form of triangular fuzzy numbers to be use d in the model. Besides that, proofs of the theorems are presented. An algorithm using the concept of fuzzy modelling is developed. The effectiveness of the es timators for this model is investigated. Monte Carl o simulation revealed that consistency depends on ban dwidth parameter. When bandwidth parameters, c are increased from 0.1, 0.5, 0.75 and 1 as the numbers of N increased (from 100 to 200 and increased to 50 0), the values of mean approaches (closed to) the real para meter. Through the bandwidth parameter also reveals that the estimated parameter is efficient, i.e., the S.D , MSE and RMSE values become smaller as N increased. In particular, the estimated parameter becomes consist ent and efficient as the bandwidth parameters appro aches to infinity, c→∞ as the number of observations, n tend to infinity, n→∞.

ESTIMATED AND ANALYSIS OF THE RELATIONSHIP BETWEEN THE ENDOGENOUS AND EXOGENOUS VARIABLES USING FUZZY SEMI-PARAMETRIC SAMPLE SELECTION MODEL