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Surveys have long been critical tools for understanding elections and forecasting their results. As the number of election surveys has increased in prevalence, researchers, journalists, and standalone political bloggers have sought to learn from the wealth of information released. This paper explores three central strategies for pooling surveys and other information to better understand both the state of an election and what can be expected when voters head to the polls. Aggregation, predictive modeling, and hybrid models are assessed as ways of improving on the results of individual surveys. For each method, central questions, key choices, applications, and considerations for use are discussed. Trade-offs in choices between pooling strategies are considered, and the accuracies of each set of strategies for forecasting results in 2012 are compared. Although hybrid models have the potential to most accurately pool election information and make predictions, the simplicity of aggregations and the theory-testing capacity of predictive models can sometimes prove more valuable.
