Data Science seminar

Title: Network Experiments for Optimal Tax Audit Policies

Location: University of Illinois Chicago

Date: Tuesday, November 19th, 2024 at 11:00 am CT at SEO 636

Professor Panagiotis Toulis 
University of Chicago
Booth School of Business

Abstract:

In this paper, we present an ongoing large field experiment in collaboration with the Tax Authority in a country of South America and the Inter-American Development Bank. The experiment randomizes tax audit notices (treatment) to firms connected through a large network determined by inter-firm VAT transactions. While the ultimate goal is to optimize tax audit policy, the short-term goal is to estimate causal effects of tax audit notices on firm behavior. Of particular interest is to understand spillovers, that is, the response of firms that are not treated but are connected to other firms that are treated. We argue that current popular approaches to experimenting on networks are limited by the reality of inter-firm networks, such as their size, high interconnectivity and heavy-tailed degree distributions. Our approach to experimentation leverages subtle sub-structures in the network and allows the application of Fisherian-style permutation tests of causal effects. These testing procedures can be computationally efficient and finite-sample valid, qualities that are important for testing in a robust way the treatment effects from complex policy interventions.

Bio:

Panos Toulis is an Associate Professor of Econometrics and Statistics at the University of Chicago Booth School of Business. He studies causal inference in complex settings (e.g., networks) through resampling methods such as permutation tests. These methods are model-agnostic and thus have a degree of robustness not afforded by classical model-based statistical methods. He is also interested in the design of experiments on networks, and generally the interface between statistics and optimization. His research has been published in the Journal of the Royal Statistical Society, Annals of Statistics, Biometrika, Journal of the American Statistical Association, Journal of Econometrics, Statistics and Computing, and Games and Economic Behavior, as well as in major machine learning and economics conferences

Hosted by: Professor Elena Zheleva