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.
In a randomized control trial, the precision of an average treatment eﬀect estimator and the power… Continue reading.
There exists a useful framework for jointly implementing Durbin-Wu-Hausman exogeneity and Sargan-Hansen overidentication tests, as a… Continue reading.
This paper describes a method for carrying out non-asymptotic inference on partially identified parameters that are… Continue reading.
To perform Bayesian analysis of a partially identified structural model, two distinct approaches exist: standard Bayesian… Continue reading.
Econometrics has traditionally revolved around point identication. Much effort has been devoted to finding the weakest… Continue reading.
We propose a bootstrap-based calibrated projection procedure to build confidence intervals for single components and for… Continue reading.
This paper derives conditions under which preferences and technology are nonparametrically identiﬁed in hedonic equilibrium models,… Continue reading.
This paper considers inference for a function of a parameter vector in a partially identiﬁed model… Continue reading.
Graphical models have become a very popular tool for representing dependencies within a large set of… Continue reading.
Due to the increasing availability of high-dimensional empirical applications in many research disciplines, valid simultaneous inference… Continue reading.
We study a panel data model with general heterogeneous eﬀects, where slopes are allowed to be… Continue reading.
This paper studies inference on treatment effects in aggregate panel data settings with a single treated… Continue reading.
The relationship between democracy and economic growth is of long standing interest. We revisit the panel… Continue reading.
We consider off-policy evaluation and optimization with continuous action spaces. We focus on observational data where… Continue reading.
This paper develops identiﬁcation and estimation methods for dynamic structural models when agents’ actions are unobserved… Continue reading.
This paper introduces measures for how each moment contributes to the precision of the parameter estimates… Continue reading.
We propose a robust method of discrete choice analysis when agents’ choice sets are unobserved. Our… Continue reading.
We develop methods for robust Bayesian inference in structural vector autoregressions (SVARs) where the impulse responses… Continue reading.
We study nonparametric estimation of density functions for undirected dyadic random variables (i.e., random variables deﬁned… Continue reading.
This paper studies the properties of the wild bootstrap-based test proposed in Cameron et al. (2008)… Continue reading.