Regulatory policy in sports betting markets is motivated by concerns that demand may be distorted by behavioral biases. We conducted a field test with casual sports bettors to measure the impact of two biases, overconfidence about financial returns and self-control problems, on the demand for sports betting. We find widespread over-optimism about financial returns. The average bettor predicts they will break even, but actually loses 7.5 cents for every dollar bet. We also find evidence of significant self-control problems, although these are smaller than overdependence. We estimate a biased betting model and use it to evaluate several adjustment policies. Our estimates mean that the tax reform that increases the tax on sports betting is twice as large as the existing tax rates. We estimate a large variation in bias across all bettors, meaning that targeted interventions that directly eliminate bias may improve taxonomy. However, removing bias is a challenge: we show that two remedial interventions favored by the gambling industry are ineffective.
That’s according to a new paper by Matthew Brown, Nick Grasley, and Mariana Guido. Matthew Brown is a candidate in the job market from Stanford, and he has a very interesting and extensive portfolio.
I don’t like, by the way, the ban on sports betting, but it’s worth asking, if it’s worth it, what the utilitarian costs of one’s libertarianism are. In this particular case, I will say “climbing!”
Source link