170 citations · 253 across the 7 of their papers we have counts for
10 papers
Simple Standard Errors for Complicated (Quasi-)Experimental Designs
Sylvia Klosin, Jonathan Roth
We develop standard errors for estimates of causal effects in settings where the distribution of treatment exposures is known but potentially exhibits complicated dependence patter…
Logs with zeros? Some problems and solutions
Jiafeng Chen, Jonathan Roth
When studying an outcome that is weakly-positive but can equal zero (e.g. earnings), researchers frequently estimate an average treatment effect (ATE) for a "log-like" transfor…
What's Trending in Difference-in-Differences? A Synthesis of the Recent Econometrics Literature
Jonathan Roth, Pedro H. C. Sant'Anna, Alyssa Bilinski +1
This paper synthesizes recent advances in the econometrics of difference-in-differences (DiD) and provides concrete recommendations for practitioners. We begin by articulating a si…
An Outcome Test of Discrimination for Ranked Lists
Jonathan Roth, Guillaume Saint-Jacques, YinYin Yu
This paper extends Becker (1957)'s outcome test of discrimination to settings where a (human or algorithmic) decision-maker produces a ranked list of candidates. Ranked lists are p…
Efficient Estimation for Staggered Rollout Designs
Jonathan Roth, Pedro H. C. Sant'Anna
We study estimation of causal effects in staggered rollout designs, i.e. settings where there is staggered treatment adoption and the timing of treatment is as-good-as randomly ass…
When Is Parallel Trends Sensitive to Functional Form?
Jonathan Roth, Pedro H. C. Sant'Anna
This paper assesses when the validity of difference-in-differences depends on functional form. We provide a novel characterization: the parallel trends assumption holds under all s…
Design-Based Uncertainty for Quasi-Experiments
Ashesh Rambachan, Jonathan Roth
Design-based frameworks of uncertainty are frequently used in settings where the treatment is (conditionally) randomly assigned. This paper develops a design-based framework suitab…
Inference for Linear Conditional Moment Inequalities
Isaiah Andrews, Jonathan Roth, Ariel Pakes
We show that moment inequalities in a wide variety of economic applications have a particular linear conditional structure. We use this structure to construct uniformly valid confi…
Bias In, Bias Out? Evaluating the Folk Wisdom
Ashesh Rambachan, Jonathan Roth
We evaluate the folk wisdom that algorithmic decision rules trained on data produced by biased human decision-makers necessarily reflect this bias. We consider a setting where trai…
Should We Adjust for the Test for Pre-trends in Difference-in-Difference Designs?
Jonathan Roth
The common practice in difference-in-difference (DiD) designs is to check for parallel trends prior to treatment assignment, yet typical estimation and inference does not account f…