Estimated and analysis of the relationship between the endogenous and exogenous variables using fuzzy semi-paranetric sample selection model
An important progress within the last decade in the development of the selectivity model approach to overcome the inconsistent results if the distributional assumptions of the errors terms are made this problem is through the use of semi-parametric method. However, the uncertainties and ambiguitie...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English English |
| Published: |
Science Publications
2014
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/40312/1/Safiih_Anton_AOMT_AJAS-ESTIMATED_AND_ANALYSIS_OF_THE_RELATIONSHIP_BETWEEN_THE_ENDOGENOUS_AND_EXOGENOUS_VARIABLES_USING_FUZZY_SEMI-PARAMETRIC_SAMPLE_SELECTION_MODEL.pdf http://irep.iium.edu.my/40312/4/40312_Estimated%20and%20analysis%20of%20the%20relationship_Scopus.pdf http://irep.iium.edu.my/40312/ http://www.thescipub.com/ajas.toc |
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| Summary: | An important progress within the last decade in the development of the selectivity model approach to
overcome the inconsistent results if the distributional 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 models,
particularly the relationship between the endogenous 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 hybrid
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 used 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 estimators for this model is investigated. Monte Carlo
simulation revealed that consistency depends on bandwidth 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 500), the
values of mean approaches (closed to) the real parameter. 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 consistent and efficient as the bandwidth parameters approaches
to infinity, c®¥ as the number of observations, n tend to infinity, n®¥.
Keywords: Selectivity Model, Semi-Parametric, Fuzzy Concept, Bandwidth, Monte Carlo |
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