If revenues are any barometer, state-run lotteries are among the most popular forms of entertainment in the United States. Such lotteries brought in more than $83 billion in the US in fiscal 2019, according to the North American Association of State and Provincial Lotteries—dwarfing, for example, the $11.4 billion North American moviegoers spent at the box office. Lotteries generate significant sums for public-sector priorities such as education and health care. But they are also a form of legalized gambling, which means they could do disproportionate harm to people with gambling addictions or few resources. So do state-run lotteries improve social welfare on balance? Chicago Booth’s Initiative on Global Markets put that question to its US Economic Experts Panel, and finds that a plurality of panelists are uncertain (meaning they believe that the evidence is ambiguous), with a significant minority on either end arguing for or against lotteries as a prosocial force.

Several panelists supplemented their answers with links to supporting research. Chicago Booth’s Anil K. Kashyap and Stanford’s Peter J. Klenow each referred to (different) papers by University of Maryland’s Melissa Schettini Kearney about the effects of legalized gambling and lotteries (the latter coauthored with Northwestern’s Jonathan Guryan). Darrell Duffie of Stanford pointed toward his own research on speculative trading to inform his opinion.

Robert Hall, Stanford
“I’m inclined to think that government should not exploit the public’s vulnerability to gambling, but I’m also aware of counter-arguments.”
Response: Uncertain

William Nordhaus, Yale
“Among the worst of social policies.”
Response: Strongly disagree

Robert Shimer, University of Chicago
“If there were no state-run lotteries, more private institutions would enable possibly biased consumers to gamble.”
Response: Agree

Richard H. Thaler, Chicago Booth
“States giving themselves a monopoly in this business is bad for sure, but if the alternative is prohibition, is that better?”
Response: Uncertain

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