In May of 2018, the Supreme Court ruled in favor of New Jersey and struck down the federal law which made sports betting illegal. This was the Professional and Amateur Sports Protection Act (PASPA) and the ruling left it up to states to decide if they wanted to allow for sports gambling. This ruling is important because the gambling industry is estimated to generate revenue around $150 billion annually with 97% of that figure being illegal activity.
This thesis will analyze the efficiency of individual states' gambling markets under different tax rates and availability scenarios. The suggested tax rates and scenarios are obtained from a study completed by Adam Sacks and Aran Ryan of Oxford Economics in May of 2017. Their study, Economic Impact of Legalized Sports Betting, presented three different tax rates and scenarios. The tax rates are applied to Gross Gaming Revenue (GGR) along with the 0.25% federal handle tax. This tax is applied to the total amount of money wagered and is not included in my study because it is outside of the states' control. The three tax rates I will focus on are the Base Tax Rate (10%), Low Tax Rate (6.75%), and the High Tax Rate (15%). The three different scenarios include Limited, Moderate, and Convenient availability.
To test efficiency, I will use Data Envelopment Analysis (DEA) and the computer program DEAP. My decision-making units (DMUs) will be the 50 states plus Washington D.C. and the United States as a whole. Inputs will include the handle (total amount wagered), GGR (taxable income kept by sportsbooks after payouts), employment (both full and part-time jobs created by legalized gambling), and adult population (stabilized for the year). The two outputs will be tax revenue and GDP, meaning the value added by sports gambling. By completing this study on the different tax rates with different availabilities, I will be able to determine which of those will be most efficient for states overall.