Predicting discrete outcomes with the maximum score estimator: The case of the NCAA men's basketball tournament

International Journal of Forecasting

Volumn 19, Issue 2, 2003, Pages 313-317

  Caudill, Steven B ^a  

^a AUBURN UNIVERSITY   (United States)

Author keywords

Discrete choice; Forecasting; Maximum score

Indexed keywords

EID: 30244504380     PISSN: 01692070     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0169-2070(02)00008-0     Document Type: Article

References (10)

1. Boulier B.L. Stekler H.O. Are sports seedings good predictors?: An evaluation International Journal of Forecasting 15 1999 83-91
2. Carlin B.P. Improved NCAA basketball tournament modeling via point spread and team strength information The American Statistician 50 1996 39-43
3. Greene W. Econometric analysis 4th ed 2000 Prentice-HallNew Jersey
4. Manski C. The maximum score estimator of the stochastic utility model of choice Journal of Econometrics 3 1975 205-228
5. Manski C. Semiparametric analysis of discrete response: Asymptotic properties of the maximum score estimator Journal of Econometrics 27 1985 313-333
6. Manski C. Operational characteristics of the maximum score estimator Journal of Econometrics 32 1986 85-100
7. Manski C. Thompson S. Estimation of best predictors of binary response Journal of Econometrics 40 1989 97-124
8. Schwertman N.C. McCready T.A. Howard L. Probability models for the NCAA regional basketball tournament The American Statistician 45 1991 35-38
9. Schwertman N.C. Schenk K.L. Holbrook B.C. More probability models for the NCAA regional basketball tournaments The American Statistician 50 1996 34-38
10. Smith T. Schwertman N.C. Can the NCAA tournament seedings be used to predict margin of victory? The American Statistician 53 1999 94-98