My research uses micro-level data that contain traces of corrupt or criminal behavior to design and implement econometric methods that measure it.
My fields are Political Economy and Applied Microeconometrics.
I will be available for interviews at the 2021 EEA and 2022 ASSA meetings.
Job Market Paper: Detection of Irregular Assignments of Cases to Judges
Abstract: I develop tools to detect irregular assignments of cases to judges and apply them to Ecuador's judicial system. I derive the sharp bounds on the overall, court-specific, and judge-specific probabilities that a case's assignment is inconsistent with existing regulations. The bounds rely on administrative case assignment data and one, or both, of the following assumptions: (i) that certain observed case characteristics do not influence which judge a case should be assigned to, and (ii) that the probability distribution over the judges that each case should be assigned to is known (e.g. uniform, random assignment). I construct a database of all publicly-available case assignments in Ecuador's district courts, with over two million assignments from 2016 to 2020, and I find that 5% of courts and judges account for 43% and 37% of irregular assignments, respectively. Overall, at least 65 thousand assignments, 2.9%, are irregular.
Optimal Transport as a Regression Analysis Tool (with Sam Higbee, Omkar Katta and Guillaume Pouliot)
Abstract: We recognize the optimal transport problem as a natural regression analysis tool, and develop a distributionally robust optimization (DRO) implementation that accounts for sampling variation.
Measurement of Tax Evasion from Guatemalan Administrative Records