Bayesian Analysis on Engel Curves Estimation With Measurement Errors and an Instrumental Variable
用贝叶斯方法估计Working-Leser形式的恩格尔曲线，处理左右两侧的测量误差，并与广义矩方法比较，发现贝叶斯方法无需额外工具变量。
AbstractIn this article, we consider the Bayesian estimation of Engel curves specified as the Working–Leser form with the measurement errors on both the left and the right sides. It is noteworthy that in the Bayesian approach no additional variation data (i.e., instrumental variables) are required in contrast with the non-Bayesian approach. We present the Bayesian estimation procedure in both models without an instrumental variable and with an instrumental variable. We also compare our results with the generalized method of moments estimates proposed by Lewbel.KEY WORDS: Errors-in-variablesGeneralized method of moments (GMM)Markov chain Monte Carlo (MCMC)Working–Leser specification