Paulo Antonacci

I’m a joint Ph.D. candidate in Economics and Public Policy at Duke University. My main research fields are public economics, public policy, and applied econometrics/machine learning.

My job market paper — Whom Should the Taxman Visit? Evidence from Door-to-Door Tax Enforcement in Indonesia — proposes a Neyman-orthogonal estimator based on the R-learner to identify which taxpayers respond most to in-person enforcement. I use these individualized treatment-effect estimates to make transparent the trade-offs between participation-maximizing and revenue-maximizing strategies that arise from heterogeneous treatment effects. The policy implications are:

1. Targeting participation increases both the number of payers and total revenue but is highly regressive;
2. Targeting revenue yields large fiscal gains with no change in participation;
3. Standard risk-based strategies (targeting likely delinquents) deliver no improvements in either outcome.

You can find the latest version here: Job Market Paper (PDF)

My research agenda includes several ongoing and planned projects, including:

1. Low-cost digital nudges for tax compliance in Indonesia.
2. Political cycles and deforestation in Brazil.
3. The old-age security hypothesis under pension reform in Brazil.
4. Evaluation of a tax-rebate policy in Pakistan.
5. Algorithmic governance and foster-care policy in Brazil.
6. Double-robust, machine-learning methods based on pseudo-treatments identification strategy.

If you are interested in more information about any of these projects or potential collaboration please feel free to contact me at paulo.antonacci@duke.edu.