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between the estimated economic impact of the NBA All Star Game and the actual revenues reported by hotels, restaurants, and rental car agencies. The story follows up on , and in addition offers Michael Casinelli, the consultant behind the original report, an opportunity to stick a foot in his mouth.

Here鈥檚 what Casinelli has to say on the gap between his estimates and the reported figures:

鈥淲hat I鈥檓 hearing [from critics] is you have to be absolutely 100 percent accurate on a future prediction when nothing is 100 percent accurate on a future prediction,鈥� said Casinelli, who has an MBA but is not an economist.

Now, I don鈥檛 know what voices Casinelli may be hearing, but the critics here at TSE would never make such a statement, not in a million years! As economists we know all too well that predictions have forecast errors. But we have two problems with the forecast errors from economic impact studies of sports. First, they are predictably biased. Second, the size of the bias is not small. The size of the bias is an order of magnitude.

Co-blogger Vic Matheson of Holy Cross is a well known critic who is responsible (in part) for these findings. The story quotes Vic, who states that the models used in studies like Casinelli鈥檚 do 鈥渁 pretty good job of counting up the economic activity that does occur 鈥� [but] a particularly poor job of counting up activity that doesn鈥檛 occur.鈥� I think that鈥檚 fair. I should also add that Casinelli makes a valid point when he notes that the tally of actual spending at various locations around Dallas is incomplete (although I believe that filling in the missing locations is quite unlikely to make up the difference).

Casinelli鈥檚 response is one of skepticism towards 鈥渁larmist鈥� academics, and a statement to the effect that 鈥渄eferred spending eventually makes its way back into the local economy and doesn鈥檛 disappear.鈥� Perhaps the imagined return of 鈥渄eferred spending鈥� can be measured, if it exists, but I doubt it even if it does. Regardless, a defense to criticism which rests on an effect which can鈥檛 verified is a classic ploy used by those with a weak argument. Name-calling as well. Sound the alarm!

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