The random coeffcients model is an extension of the linear regression model which allows for additional heterogeneity in the population by modeling the regression coeffcients as random variables. Given data from this model, the statistical challenge is to recover information about the joint...

The random coeffcients model is an extension of the linear regression model which allows for additional heterogeneity in the population by modeling the regression coeffcients as random variables. Given data from this model, the statistical challenge is to recover information about the joint...

In this paper, we propose a doubly robust method to present the heterogeneity of the average treatment effect with respect to observed covariates of interest. We consider a situation where a large number of covariates are needed for identifying the average treatment effect but the covariates of...

We derive strong approximations to the supremum of the non-centered empirical process indexed by a possibly unbounded VC-type class of functions by the suprema of the Gaussian and bootstrap processes. The bounds of these approximations are non-asymptotic, which allows us to work with classes of...

We derive strong approximations to the supremum of the non-centered empirical process indexed by a possibly unbounded VC-type class of functions by the suprema of the Gaussian and bootstrap processes. The bounds of these approximations are non-asymptotic, which allows us to work with classes of...

In this paper, we propose a doubly robust method to present the heterogeneity of the average treatment effect with respect to observed covariates of interest. We consider a situation where a large number of covariates are needed for identifying the average treatment effect but the covariates of...