A new approach to estimating the probability of winning the presidency

Operations Research

Volumn 51, Issue 1, 2003, Pages

  Kaplan, Edward H ^a   Barnett, Arnold ^b  

^a YALE SCHOOL OF MANAGEMENT   (United States)

^b MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Government: elections, electoral college; Probability: stochastic model applications; Statistics: Bayesian, sampling

Indexed keywords

ELECTIONS; ELECTORAL COLLEGE; PUBLIC SECTOR;

COMPUTER SIMULATION; DATA REDUCTION; PROBABILITY; RANDOM PROCESSES; RELIABILITY; SAMPLING;

OPERATIONS RESEARCH;

EID: 4243105161     PISSN: 0030364X     EISSN: None     Source Type: Journal    
DOI: 10.1287/opre.51.1.32.12794     Document Type: Article

References (5)

1. Box, G. E. P., G. C. Tiao. 1973. Bayesian Inference in Statistical Analysis. Addison-Wesley, Reading, MA.
2. Erikson, R. S., K. Sigman. 2000. A simple stochastic model for close U.S. presidential elections. Working paper, Department of Political Science, Columbia University, New York.
3. Jackman, S., D. Rivers. 2001. State-level election forecasting during Election 2000 via dynamic Bayesian hierarchical modeling. Working paper, Department of Political Science, Stanford University, Stanford, CA.
4. Jeffreys, H. 1961. Theory of Probability, 3rd ed. Clarendon Press, Oxford, U.K.
5. Raiffa, H., R. Schlaifer. 1968. Applied Statistical Decision Theory. MIT Press, Cambridge, MA.