Fuzzy approach to semi-parametric of a sample selection model

  • Authors:

  • L. Muhamad Safiih;A. A. Basah Kamil;M. T. Abu Osman

  • Affiliations:

  • Mathematics Department, Faculty of Science and Technology, University Malaysia Terengganu, Terengganu, Malaysia;School of Distance Learning, Universiti Sains Malaysia, Malaysia;Mathematics Department, Faculty of Science and Technology, University Malaysia Terengganu, Terengganu, Malaysia

  • Venue:
  • WSEAS Transactions on Mathematics
  • Year:
  • 2008

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Abstract

The sample selection model is studied in the context of semi-parametric methods. With the deficiency of the parametric model, such as inconsistent estimators etc, the semi-parametric estimation methods provide the best alternative to handle this deficiency. Semi-parametric of a sample selection model is an econometric model and has found interesting application in empirical studies. The issue of uncertainty and ambiguity still become are still major problem and are complicated in the modelling of a semi-parametric sample selection model as well as its parametric. This study, focuses on the context of fuzzy concept as a hybrid to the semi-parametric sample selection model. The best approach of accounting for uncertainty and ambiguity is to take advantage of the tools provided by the theory of fuzzy sets. It seems particularly appropriate for modelling vague concepts. Fuzzy sets theory and its properties, through the concept of fuzzy number, provide an ideal framework in order to solve the problem of uncertain data. In this paper, we introduce a fuzzy membership function for solving uncertain data of a semi-parametric sample selection model.