Semiparametric Bayesian inference for dynamic Tobit panel data models with unobserved heterogeneity
含不可观测异质性的动态 Tobit 面板模型:半参数贝叶斯推断
Abstract This paper develops semiparametric Bayesian methods for inference of dynamic Tobit panel data models. Our approach requires that the conditional mean dependence of the unobserved heterogeneity on the initial conditions and the strictly exogenous variables be specified. Important quantities of economic interest such as the average partial effect and average transition probabilities can be readily obtained as a by‐product of the Markov chain Monte Carlo run. We apply…