no code implementations • 8 May 2024 • Eric Auerbach, Annie Liang, Max Tabord-Meehan, Kyohei Okumura
In this paper, we provide an econometric framework for testing the hypothesis that it is possible to improve on the fairness of an algorithm without compromising on other pre-specified objectives.
no code implementations • 9 Apr 2024 • Eric Auerbach, Yong Cai, Ahnaf Rafi
Under the assumption that spillovers are linear-in-means, we show that the estimand depends on the ratio of two terms: (1) the radius over which spillovers occur and (2) the choice of bandwidth used for the local linear regression.
no code implementations • 11 Jan 2024 • Eric Auerbach, Jonathan Auerbach, Max Tabord-Meehan
We thank Savje (2023) for a thought-provoking article and appreciate the opportunity to share our perspective as social scientists.
1 code implementation • 26 Jun 2023 • Eric Auerbach, Yong Cai
Social disruption occurs when a policy creates or destroys many network connections between agents.
1 code implementation • 2 May 2022 • Eric Auerbach, Yong Cai
We then propose a new matrix analog of quantile treatment effects that is given by a difference in the eigenvalues.
no code implementations • 20 May 2021 • Eric Auerbach
This paper provides additional results relevant to the setting, model, and estimators of Auerbach (2019a).
no code implementations • 9 May 2021 • Eric Auerbach, Max Tabord-Meehan
We propose a new nonparametric modeling framework for causal inference when outcomes depend on how agents are linked in a social or economic network.
1 code implementation • 16 Jan 2020 • Hossein Alidaee, Eric Auerbach, Michael P. Leung
Breza et al. (2017) propose aggregated relational data (ARD) as a low-cost substitute that can be used to recover the structure of a latent social network when it is generated by a specific parametric random effects model.
no code implementations • 22 Mar 2019 • Eric Auerbach
In this paper, I describe the model, formalize this intuition, and provide consistent estimators for the parameters of the regression model.