Research
Illegal Drug Markets
Illegal Drug Use and Government Policy: Evidence from a Darknet Marketplace
with Priyanka Goonetilleke, Anastasia Karpova, and Peter Meylakhs, Job Market Paper
Abstract:
This paper develops a structural model of demand for illegal drugs to study how consumers substitute between drugs in response to government policies. We construct a unique dataset by scraping a darknet marketplace that dominated the retail illegal drug trade in Russia. We exploit novel micro-level moment conditions and estimate a median demand elasticity of -1.9. Using the estimated model, we show that after cannabis legalization, for every four additional doses of cannabis, one fewer dose of another drug is consumed. We also find that new synthetic drugs sharply increased total drug demand and that enforcement can raise drug-market revenue.
Hydra: Lessons from the World’s Largest Darknet Market
with Priyanka Goonetilleke and Alex Knorre, Criminology & Public Policy, November 2023
Abstract
We present a comprehensive description of Hydra, the largest darknet marketplace in the world until its shutdown in April 2022. Using data scraped from the platform, we quantitatively examine the scale and the structure of the marketplace. We find that it has been highly competitive, geographically covering at least 69% of the Russian population and trading a wide variety of drugs, while also allowing the wholesale trade of drugs and precursors. We propose a model to estimate the delivery costs and find that they comprised a substantial proportion of the sale price of drugs on Hydra. The phenomenon of Hydra shows that shut-down policies applied to darknet marketplaces have a large effect and implicitly shape the whole drug market. Without these policies, a pervasive digitalization of drug trade can occur.
Online Drug Markets and Implications for Addiction Medicine: A Narrative Literature Review
with Nicolas Garel, Priyanka Goonetilleke, and Steven Tate, Journal of Addiction Medicine, April 2025
Abstract
This narrative review examines the evolving landscape of online drug markets, focusing on darknet markets for illegal drugs and their implications for addiction medicine. We provide an overview of the development and current state of these markets, highlighting key features of their operation and the demographics of users. Finally, we address the implications for addiction medicine clinicians, including the need for adapted prevention efforts, new approaches to intervention and relapse prevention, and the potential for leveraging digital platforms in treatment. This review aims to equip addiction medicine professionals with the knowledge needed to navigate the challenges posed by online drug markets and to enhance their ability to provide effective care in this changing environment.Experimentation
Network Experiments with Edge Treatments and Node Outcomes
with Kenneth Hung, arXiv:2610.07363
Abstract
We present a methodology for analyzing node-level outcomes while experimenting with edge-level treatments in a population connected by an undirected graph. Under our design, nodes are randomly assigned to test or control, and each edge inherits the treatment of its endpoints, with conflicts resolved by randomization. We use each node's assigned status as an instrument for its treatment exposure. We show that the Wald estimator is consistent for the global average treatment effect (GATE), even when the edge weights used to construct the exposure are misspecified. We formalize the assumptions needed both in terms of the linearity of potential outcomes and the sparsity of the graph, and prove the asymptotic normality of the Wald estimator. The estimator is straightforward to implement, requiring no assignment simulations over the graph. Our Monte Carlo study demonstrates the strong performance of our approach in the context of a social platform.AI and Economic Modeling
An Economy of Neural Networks: Learning from Heterogeneous Experiences
PIER Working Paper No. 21-027