597 citations · 1.3k across the 13 of their papers we have counts for
13 papers
Labour by Design: Contributions of David Card, Joshua Angrist, and Guido Imbens
Peter Hull, Michal Kolesár, Christopher Walters
The 2021 Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel was awarded to David Card "for his empirical contributions to labour economics" and to Joshua Angris…
When Can We Ignore Measurement Error in the Running Variable?
Yingying Dong, Michal Kolesár
In many applications of regression discontinuity designs, the running variable used by the administrator to assign treatment is only observed with error. We show that, provided the…
One Instrument to Rule Them All: The Bias and Coverage of Just-ID IV
Joshua Angrist, Michal Kolesár
We revisit the finite-sample behavior of single-variable just-identified instrumental variables (just-ID IV) estimators, arguing that in most microeconometric applications, the usu…
Contamination Bias in Linear Regressions
Paul Goldsmith-Pinkham, Peter Hull, Michal Kolesár
We study regressions with multiple treatments and a set of controls that is flexible enough to purge omitted variable bias. We show that these regressions generally fail to estimat…
Bias-Aware Inference in Regularized Regression Models
Timothy B. Armstrong, Michal Kolesár, Soonwoo Kwon
We consider inference on a scalar regression coefficient under a constraint on the magnitude of the control coefficients. A class of estimators based on a regularized propensity sc…
Robust Empirical Bayes Confidence Intervals
Timothy B. Armstrong, Michal Kolesár, Mikkel Plagborg-Møller
We construct robust empirical Bayes confidence intervals (EBCIs) in a normal means problem. The intervals are centered at the usual linear empirical Bayes estimator, but use a crit…
Sensitivity Analysis using Approximate Moment Condition Models
Timothy B. Armstrong, Michal Kolesár
We consider inference in models defined by approximate moment conditions. We show that near-optimal confidence intervals (CIs) can be formed by taking a generalized method of momen…
Shift-Share Designs: Theory and Inference
Rodrigo Adão, Michal Kolesár, Eduardo Morales
We study inference in shift-share regression designs, such as when a regional outcome is regressed on a weighted average of sectoral shocks, using regional sector shares as weights…
Finite-Sample Optimal Estimation and Inference on Average Treatment Effects Under Unconfoundedness
Timothy B. Armstrong, Michal Kolesár
We consider estimation and inference on average treatment effects under unconfoundedness conditional on the realizations of the treatment variable and covariates. Given nonparametr…
Inference in Regression Discontinuity Designs with a Discrete Running Variable
Michal Kolesár, Christoph Rothe
We consider inference in regression discontinuity designs when the running variable only takes a moderate number of distinct values. In particular, we study the common practice of…
Simple and Honest Confidence Intervals in Nonparametric Regression
Timothy B. Armstrong, Michal Kolesár
We consider the problem of constructing honest confidence intervals (CIs) for a scalar parameter of interest, such as the regression discontinuity parameter, in nonparametric regre…
Optimal inference in a class of regression models
Timothy B. Armstrong, Michal Kolesár
We consider the problem of constructing confidence intervals (CIs) for a linear functional of a regression function, such as its value at a point, the regression discontinuity para…
A Simple Adjustment for Bandwidth Snooping
Timothy B. Armstrong, Michal Kolesár
Kernel-based estimators such as local polynomial estimators in regression discontinuity designs are often evaluated at multiple bandwidths as a form of sensitivity analysis. Howeve…