How is grand-scale research on lottery advertising like grand-scale research in agriculture? No one does it, who must thrive or fail according to the outcome. With my friend Jade I discuss tests of smaller scale, and we agree that there is usually something to be learned from a well-constructed test of advertising, even if the results are not what everyone wanted. After all, don’t we want to know what not to do? NASPL Insights August 2017
After January 2016, we saw sales for jackpots in the range $200 to $400 million significantly lower than before. My math models support estimating the effect of these changes on the development of big jackpots in the future. I estimate the likelihood of a jackpot reaching $1 billion in 2017 at about 10%, down from about 17% at the start of 2016. NASPL Insights December 2016
I combined data from two sources to get a view of how much the “average citizen” lost in legal gambling, across 41 U.S. jurisdictions. The per capita annual loss to lottery is much more variable than the loss to all legal gambling combined. Lottery thrives in states where other legal gambling is limited (and even in neighbors of those states). Total annual per capita losswhich seldom exceeds $500 per capita annually. The potential for improved lottery yields is likely constrained by this combined limit. All Legal Gambling 2016
NASPL Insights December 2014, I assessed the behavior of the Powerball and Mega Millions games in the eleven months since California joined the Powerball game. I found that while sales at jackpots below $100 million had remained fairly steady, the sales response to jackpots approaching $300 million was less than half what it had been during the “base period” between Feb 2012 (when Powerball raised its price to $2) and April 2013 (when California joined). I went on to project the probability distribution for jackpots greater than $300 million in the coming year. The difference between the games was stark: Powerball was more likely than not to have three or more such events, while Mega Millions was more likely than not to have no more than one.