IV methods for Tobit models
研究了当结果变量存在左删失且解释变量内生时，如何利用工具变量进行推断，不依赖控制函数假设，可得到部分或点识别，并用英国家庭烟草支出数据演示了方法。
This paper studies models of processes generating censored outcomes with endogenous explanatory variables and instrumental variable restrictions. Tobit-type left censoring at zero is the primary focus in the exposition. Extension to stochastic censoring is sketched. The models do not specify the process determining endogenous explanatory variables and they do not embody restrictions justifying control function approaches. Consequently, they can be partially or point identifying. Identified sets are characterized and it is shown how inference can be performed on scalar functions of partially identified parameters when exogenous variables have rich support. In an application using data on UK household tobacco expenditures inference is conducted on the coefficient of an endogenous total expenditure variable with and without a Gaussian distributional restriction on the unobservable and compared with the results obtained using a point identifying complete triangular model.