3 citations · 4 across the 4 of their papers we have counts for
5 papers
Representation Risk in Pretrained Image Encoders
Ardyn Nordstrom, Morgan Nordstrom, Vamuyan Sesay +1
Applied researchers increasingly convert images into features with pretrained encoders, then use those features in a downstream prediction model. The encoder is often treated as an…
Which Policy Works, and Where? Estimation and Inference for State-Level Treatment Effects in Difference-in-Differences
Nichole Austin, Sunny R. Karim, Erin Strumpf +1
Policies with a common objective and implementation date may differ in details or context. We distinguish the aggregate average treatment effect on the treated (ATT) from sub-aggre…
Good Controls Gone Bad: Difference-in-Differences with Covariates
Sunny Karim, Matthew D. Webb
This paper introduces the common causality of covariates (CCC) assumption in difference-in-differences with covariates. This assumption stipulates that covariates must have common…
Using Images as Covariates: Measuring Curb Appeal with Deep Learning
Ardyn Nordstrom, Morgan Nordstrom, Matthew D. Webb
This paper details an innovative methodology to integrate image data into traditional econometric models. Motivated by forecasting sales prices for residential real estate, we harn…
Difference-in-Differences with Unpoolable Data
Sunny Karim, Matthew D. Webb, Nichole Austin +1
Difference-in-differences (DID) is commonly used to estimate treatment effects but is infeasible in settings where data are unpoolable due to privacy concerns or legal restrictions…