Estimation with Errors in Variables via the Characteristic Function
提出用特征函数估计线性模型中变量含误差的参数，假设解释变量服从双伽马分布得到解析式，模拟显示优于现有方法，并推广到多元情形，用资本资产定价模型和两因子模型验证。
Abstract Errors in variables in linear regression continue to be a significant empirical issue in financial econometrics. We propose using the characteristic function (CF) to obtain estimates for linear models with errors in the variables. By assuming that the explanatory variable follows a flexible double gamma distribution, we obtain closed-form expressions for the analytic CF of the data generating process. We show that our method performs well relative to existing techniques that address error-in-variables (EIVs) through simulations. We further extend our CF technique to a multivariate setting where it continues to produce accurate estimates. We illustrate the performance of our procedure by estimating the capital asset pricing model and a two-factor model.