The cemmap working paper series publishes papers expanding the frontiers of knowledge in microdata methods and practice. Martin Weidner is the editor of the working paper series.
This paper develops a new direct approach to approximating suprema of general empirical processes by a… Continue reading.
This paper considers the problem of testing many moment inequalities where the number of moment inequalities,… Continue reading.
Modern construction of uniform confidence bands for nonpara-metric densities (and other functions) often relies on the… Continue reading.
This paper develops characterizations of identifi ed sets of structures and structural features for complete and incomplete… Continue reading.
Advances in the study of partial identification allow applied researchers to learn about parameters of interest… Continue reading.
Quantile regression (QR) is a principal regression method for analyzing the impact of covariates on outcomes…. Continue reading.
In this paper, we derive a rate of convergence of the Lasso estimator when the penalty… Continue reading.
The ill-posedness of the inverse problem of recovering a regression function in a nonparametric instrumental variable… Continue reading.
Most modern supervised statistical/machine learning (ML) methods are explicitly designed to solve prediction problems very well…. Continue reading.
This paper models the use of statistical hypothesis testing in regulatory approval. A privately informed agent… Continue reading.
Recent developments in nonlinear panel data analysis allow identifying and estimating general dynamic systems. In this… Continue reading.
We propose a Kronecker product structure for large covariance or correlation matrices. One feature of this… Continue reading.
We consider a class of nonparametric time series regression models in which the regressor takes values… Continue reading.
This paper provides a framework for identifying preferences in a large network where links are pairwise… Continue reading.