基于局部线性工具变量的半参数模型估计方法研究

Researches on Semiparametric Model Estimation Method Based on Local Linear Instrumental Variables

  • 摘要: 本文针对半参数模型中工具变量求解方法,考虑到传统工具变量需要特定假设的狭隘性,提出不需要假定特定的误差模型或者已知误差,并将其命名为SEMI-LWLR-IV估计。首先通过局部线性进行工具变量拟合矫正,之后使用得到的矫正估计值对半参数模型进行估计.之后给出无偏性与渐近正态性的定理及其证明.随后,本文通过蒙特卡洛方法生成数据,使用新估计方法对生成数据拟合,拟合结果表明,在工具变量与内生变量呈线性关系时,新的估计方法与传统2SLS估计结果基本一致;在工具变量与内生变量呈非线性关系时,新方法具有比已有方法更优良的性质.

     

    Abstract: Considering the weak instrumental variables, aiming at the solution method of instrumental variables in the semi parametric model, the paper creatively introduces the local linear estimation in the nonparametric estimation into the two-stage instrumental variable estimation, and names it SEMI-LWLR-IV estimation. After which, the paper gives the unbiased and asymptotic normality theorems and their proofs. Then, this paper uses Monte Carlo method to generate data, and uses a new estimation method to fit the generated data. The fitting results show that when the relation between instrumental variables and endogenous variables is linear, the new estimation method is basically consistent with the traditional 2SLS estimation results; When the relation between instrumental variables and endogenous variables are nonlinear, the new method has better properties than the existing methods.

     

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