Non/Semi-parametric Instrumental Variables Modelsfor Economic Data
Non/Semi-parametric Instrumental Variables Modelsfor Economic Data
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发表时间：
2008-12
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通讯作者：
Huaiyu Xiong
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作者：
Huaiyu Xiong
近年来，计量经济学家将工具变量模型（一种标准的内点回归方法）扩展到非/半参数设置。然而，当内生变量是连续的，这样的模型是暴露于不适定的问题。从一个不同的假设工作，这本书认为估计的非/半参数工具变量模型下的一个功能系数的形式。在这种表示下，模型在具有常数或未知函数系数的内源成分中是线性的。由于模型的线性性，避免了不适定问题，同时保留了回归函数的灵活性。本文构造了常系数和函数系数估计，并证明了它们的相合性和渐近正态性。这些估计的高实用功率说明通过蒙特卡罗模拟和应用劳动统计。本书为研究人员和从业者提供了一种更有效的方法，利用非/半参数模型分析具有内生变量的经济数据。
In recent years, econometricians extended instrumental variable models, a standard approach to regression with endogeneity, to non/semi-parametric settings. However, when the endogenous variables are continuous, such models are exposed to ill-posed problems. Working from a different assumption, this book considers estimation of non/semi-parametric instrumental variables models under a functional coefficient form. Under this representation, models are linear in the endogenous components with either constant or unknown functional coefficients. Due to the linearity, the models avoid the ill-posed problems and at the same time retain the flexibility of the regression function. This study constructs the constant and functional coefficients estimators and proves their consistency and asymptotic normality. The high practical power of these estimators is illustrated via Monte Carlo simulations and an application to labor statistics. The book provides a more efficient way for researchers and practitioners to analyze economic data with endogenous variables utilizing non/semi- parametric models.