Inference in Incomplete Econometric Models

这个项目开发的方法，处理经济模型的估计，同时施加最小的合理假设。特别是，该项目研究的模型类别是根据不平等限制定义的。这些不等式限制出现在具有不完整数据（删失或顶层编码的数据）的模型中，在具有多重均衡的模型中，或者在具有测量误差的模型中。所开发的估计技术首先应用于具有内点的区间数据的估计问题。 第二，该方法被用来获得更强大的英国拍卖模型与出价数据的推断。第三，将该方法应用于具有测量误差的非线性模型。该项目还将研究构建有效测试的问题，使这些模型的估计组件的置信区域。

This project develops methods that deal with estimation of economic models while imposing minimum plausible assumptions. In particular, the class of models that the project examines are defined in terms of inequality restrictions. These inequality restrictions arise in models with incomplete data (data that are censored or top-coded), in models with multiple equilibria, or in models with measurement error, among others. The estimation techniques that are developed are applied first in estimation problems with interval data with endogeneity. Second, the methods are used to obtain more robust inference in English auction models with bids data. Third, the methods are applied to nonlinear models with measurement error. The project will also examine the issue of constructing valid tests that enables confidence regions for the estimated components of these models.