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首页> 外文期刊>American journal of applied sciences >Fuzzy Parametric of Sample Selection Model Using Heckman Two-Step Estimation Models | Science Publications
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Fuzzy Parametric of Sample Selection Model Using Heckman Two-Step Estimation Models | Science Publications

机译：Heckman两步估计模型的样本选择模型模糊参数科学出版物

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> Problem statement: It is well known that, the standard approach to estimating a sample selection models shows an inconsistent estimation results if the distributional assumption are incorrect. Approach: An important progress in the last decade to develop an alternative to overcome the deficiency is through the used of semi-parametric method. However, the usage of semi-parametric approach still does not cover the deficiency of the model. Results: We introduced a fuzzy membership function for solving uncertainty data of a sample selection model and employed method for sample selection models, that is, the two-step estimators to estimate a model of the so-called the self-selection decision. Fuzzy Parametric of Sample Selection Model (FPSSM) is builds as a hybrid to the conventional parametric sample selection model. Conclusion/Recommendations: The result showed that as a whole, the FPSSM give a better estimate and consistent when compared to the Parametric of Sample Selection Model (PSSM). This application demonstrate that the proposed fuzzy modeling approach was quite reasonable and provides an important and significant finding compared with conventional method especially in terms of estimation and consistency.
机译： > 问题陈述：众所周知，如果分布假设不正确，估计样本选择模型的标准方法将显示不一致的估计结果。 方法：在过去十年中，开发一种克服缺陷的替代方法的重要进展是通过使用半参数方法。但是，使用半参数方法仍不能弥补模型的不足。 结果：我们引入了一种模糊隶属函数来求解样本选择模型的不确定性数据，并采用了样本选择模型的方法，即通过两步估算器来估算所谓的模型自我选择的决定。样本选择模型（FPSSM）的模糊参数是与常规参数样本选择模型的混合体。 结论/建议：结果表明，与样本选择模型参数（PSSM）相比，FPSSM总体上具有更好的估计和一致性。该应用表明，所提出的模糊建模方法是相当合理的，并且与常规方法相比，尤其是在估计和一致性方面，提供了重要而重要的发现。

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