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The Benefits of College Athletic Success: An Application of the Propensity Score Design with Instrumental Variables

  • Michael L. Anderson

Spending on big-time college athletics is often justified on the grounds that athletic success attracts students and raises donations. Testing this claim has proven difficult because success is not randomly assigned. We exploit data on bookmaker spreads to estimate the probability of winning each game for college football teams. We then condition on these probabilities using a propensity score design to estimate the effects of winning on donations, applications, and enrollment. The resulting estimates represent causal effects under the assumption that, conditional on bookmaker spreads, winning is uncorrelated with potential outcomes. Two complications arise in our design. First, team wins evolve dynamically throughout the season. Second, winning a game early in the season reveals that a team is better than anticipated and thus increases expected season wins by more than one-for-one. We address these complications by combining an instrumental variables-type estimator with the propensity score design. We find that winning reduces acceptance rates and increases donations, applications, academic reputation, in-state enrollment, and incoming SAT scores.

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File URL: http://www.nber.org/papers/w18196.pdf
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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 18196.

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Date of creation: Jun 2012
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Handle: RePEc:nbr:nberwo:18196
Note: ED LS PE
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  1. Meer, Jonathan & Rosen, Harvey S., 2009. "The impact of athletic performance on alumni giving: An analysis of microdata," Economics of Education Review, Elsevier, vol. 28(3), pages 287-294, June.
  2. Yoav Benjamini & Abba M. Krieger & Daniel Yekutieli, 2006. "Adaptive linear step-up procedures that control the false discovery rate," Biometrika, Biometrika Trust, vol. 93(3), pages 491-507, September.
  3. David Card & Gordon Dahl, 2009. "Family Violence and Football: The Effect of Unexpected Emotional Cues on Violent Behavior," NBER Working Papers 15497, National Bureau of Economic Research, Inc.
  4. LaLonde, Robert J, 1986. "Evaluating the Econometric Evaluations of Training Programs with Experimental Data," American Economic Review, American Economic Association, vol. 76(4), pages 604-20, September.
  5. Tucker, Irvin B., 2004. "A reexamination of the effect of big-time football and basketball success on graduation rates and alumni giving rates," Economics of Education Review, Elsevier, vol. 23(6), pages 655-661, December.
  6. Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2003. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," Econometrica, Econometric Society, vol. 71(4), pages 1161-1189, 07.
  7. Steven D. Levitt, 2004. "Why are gambling markets organised so differently from financial markets?," Economic Journal, Royal Economic Society, vol. 114(495), pages 223-246, 04.
  8. Murphy, Robert G. & Trandel, Gregory A., 1994. "The relation between a university's football record and the size of its applicant pool," Economics of Education Review, Elsevier, vol. 13(3), pages 265-270, September.
  9. A. Smith, Jeffrey & E. Todd, Petra, 2005. "Does matching overcome LaLonde's critique of nonexperimental estimators?," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 305-353.
  10. Sarah E. Turner & Lauren A. Meserve & William G. Bowen, 2001. "Winning and Giving: Football Results and Alumni Giving at Selective Private Colleges and Universities," Social Science Quarterly, Southwestern Social Science Association, vol. 82(4), pages 812-826.
  11. Devin G. Pope & Jaren C. Pope, 2009. "The Impact of College Sports Success on the Quantity and Quality of Student Applications," Southern Economic Journal, Southern Economic Association, vol. 75(3), pages 750–780, January.
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