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 considers the finite sample distribution of the 2SLS estimator and derives bounds on its… Continue reading.
A new bandwidth selection rule that uses different bandwidths for the local linear regression estimators on… Continue reading.
I formulate and study a model of undirected dyadic link formation which allows for assortative matching… Continue reading.
Often semiparametric estimators are asymptotically equivalent to a sample average. The object being averaged is referred… Continue reading.
This paper studies inference for the average treatment effect in randomized controlled trials with covariate-adaptive randomization…. Continue reading.
In the practice of program evaluation, choosing the covariates and the functional form of the propensity… Continue reading.
Empirical models of demand for – and, often, supply of – differentiated products are widely used… Continue reading.
We present new results on the identifiability of a class of nonseparable nonparametric simultaneous equations models… Continue reading.
A new bandwidth selection method for the fuzzy regression discontinuity estimator is proposed. The method chooses… Continue reading.
This paper studies the nonparametric identification and estimation of voters’ preferences when voters are ideological. We… Continue reading.
This paper studies nonparametric identification in market level demand models for differentiated products. We generalize common… Continue reading.
In this article I provide a (selective) review of the recent econometric literature on networks. I… Continue reading.
We develop a new quantile-based panel data framework to study the nature of income persistence and… Continue reading.
This paper introduces a bootstrap-based inference method for functions of the parameter vector in a moment… Continue reading.
In this paper, we provide efficient estimators and honest confidence bands for a variety of treatment… Continue reading.
Common high-dimensional methods for prediction rely on having either a sparse signal model, a model in… Continue reading.
We propose new concepts of statistical depth, multivariate quantiles, vector quantiles and ranks, ranks, and signs,… Continue reading.
We propose a notion of conditional vector quantile function and a vector quantile regression. A conditional… Continue reading.
This paper examines a general class of inferential problems in semiparametric and nonparametric models defined by… Continue reading.
Medical research has evolved conventions for choosing sample size in randomized clinical trials that rest on… Continue reading.