Marijuana is the most common illicit drug with vocal advocates for legalization. Among other things, legalization would increase access and remove the stigma of illegal behavior. Our model of use disentangles the role of access from preferences and shows that selection into access is not random. We find that non-selection-corrected demand estimates are biased resulting in incorrect policy conclusions. Our results show the probability of underage use would increase by 38% and more than double in most age groups under legalization. Tax policies are effective at curbing use where over $8 billion in annual tax revenue could be realized.
Professor Michelle Sovinsky of the University of Zurich has a B.S. in Economics from George Mason University and a PhD from the University of Virginia. Her research focuses on using game-theoretic modeling with empirical analysis to examine policy issues in applied health and industrial organization, and has appeared in leading international journals including Econometrica, the International Economic Review and Journal of Human Resources. Michelle's research covers a wide range of topics including long-term care for the elderly; how individuals make risky decisions concerning their health, drug use, or eating behaviors; individual-decision making under limited information; and the antitrust implications of research collaboration or advertising expenditures. Professor Sovinsky has a number of international affiliations including the University of Chicago and the UK based Centre for Economic Policy Research.
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