Title:      Bayesian Model Averaging: Theoretical developments
and practical applications

Authors:    Jacob Montgomery, Brendan Nyhan

Entrydate:  2008-01-22 17:43:17

Keywords:   Bayesian model averaging, BMA, model robustness,
specification uncertainty

Abstract:   Political science researchers typically conduct an
idiosyncratic search of possible model configurations and then
present a single specification to readers. This approach
systematically understates the uncertainty of our results,
generates concern among readers and reviewers about fragile
model specifications, and leads to the estimation of bloated
models with huge numbers of controls. Bayesian model averaging
(BMA) offers a systematic method for analyzing specification
uncertainty and checking the robustness of one's results to
alternative model specifications. In this paper, we summarize
BMA, review important recent developments in BMA research, and
argue for a different approach to using the technique in
political science. We then illustrate the methodology by
reanalyzing models of voting in U.S. Senate elections and
international civil war onset using software that respects
statistical conventions within political science.

http://polmeth.wustl.edu/retrieve.php?id=730

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