Semiparametric Approaches to Stochastic Panel Frontiers With Applications in the Banking Industry
提出新的半参数建模与估计方法，以缓解内生性和模型设定错误问题，并应用于银行多产出随机距离前沿的估计。
This article introduces new modeling and estimation methods designed to help mitigate problems of endogeneity and misspecification. We use an output distance function to model the technology of a multioutput firm. We also use results from Park and Simar and Park, Sickles, and Simar on semiparametric efficient estimation of panel models to estimate multioutput stochastic distance frontiers, for which the distribution of the effects and a subgroup of regressors is not specified. Furthermore, we introduce a new semiparametric method that makes minimal assumptions on the functional form of inputs in the distance function.