Tanvi Shinkre

About Me

I am a PhD student in Statistics at UCLA, working on research in causal inference with Prof. Chad Hazlett. My research focuses on methods for causal effect estimation, specifically in settings with treatment effect heterogeneity and in settings where treatment is not effectively implemented. My applied projects focus on public policy settings in public health and sociology -- most recently, this has included multiple projects that examine effects of state policies on firearm-related deaths in the US. I am currently affiliated with the Practical Causal Inference Lab and the Inequality Data Science Lab at UCLA.

Working Papers

Chad Hazlett & Tanvi Shinkre. Understanding and avoiding the "weights of regression": Heterogeneous effects, misspecification, and longstanding solutions.

Jiahui Xu, Jennie E. Brand, Tanvi Shinkre, and Nanum Jeon. Flexibly Detecting Effect Heterogeneity with an Application to the Effects of College on Reducing Poverty.

Software Packages

Jiahui Xu & Tanvi Shinkre & Jennie E. Brand, 2023. htetree: Causal Inference with Tree-Based Machine Learning Algorithms.

Ravaris Moore & Jennie E. Brand & Tanvi Shinkre, 2021. "ITPSCORE: Stata module to implement Iterative Propensity Score Logistic Regression Model Search Procedure," Statistical Software Components S459018, Boston College Department of Economics, revised 24 Nov 2021.