David Powell

David Powell is a Senior Economist and Professor of Policy Analysis at the RAND School of Public Policy, RAND Corporation. He is a leading researcher in health economics, public finance, labor economics, and econometrics, with a strong focus on the opioid crisis, health insurance design, and tax policy impacts on labor and health decisions.

His research interests include:

• Health Economics and Opioid Policy
• Public Finance and Tax Responsiveness
• Labor Supply and Employment Effects
• Health Insurance Benefit Design
• Substance Use and Public Safety
• Methodological Innovations in Causal Inference

David Powell's recent research spans the evolving opioid epidemic, including naloxone access, prescription monitoring, and the unintended consequences of abuse-deterrent formulations. He has also advanced synthetic control and quantile treatment effect methods. His work often combines large-scale data analysis with rigorous econometric techniques to inform state and national policy.

His publications show a consistent focus on public health crises, labor market dynamics, and policy evaluation. Key themes include the socioeconomic determinants of overdose, the role of healthcare access in labor outcomes, and the design of effective interventions for substance use and workplace safety.

Notable scientific contributions include methodological advancements in policy evaluation and influential studies on the ripple effects of OxyContin reformulation, marijuana legalization, and health insurance design.

David Powell advises on policy tools and evaluations, particularly in motor vehicle safety and substance use interventions. His work is supported by extensive data analysis and collaboration across public health and economic domains. He is involved in developing interactive tools for policymakers to assess intervention cost-effectiveness.

He is affiliated with RAND’s research teams focused on public safety, health behavior, and modeling and simulation. His work often involves cross-institutional data and policy-relevant modeling to support evidence-based decision-making at state and federal levels.