[gov3009-l] Lok on "Bayesian Combination of State Polls and Election Forecasts"

Justin Grimmer jgrimmer at fas.harvard.edu
Mon Feb 2 14:13:55 EST 2009


Dear Applied Statistics Community,

The first meeting of the applied statistics workshop will be this Wednesday,
February 4th, when Kari Lock, Graduate Student in the Department of
Statistics, will present "Bayesian Combination of State Polls and Election
Forecasts".   Kari provided the following abstract:

A wide range of potentially useful data are available for election
forecasting: the results of previous elections, a multitude of pre-election
polls, and predictors such as measures of national and statewide economic
performance. How accurate are different forecasts? We estimate predictive
uncertainty via analysis of data collected from past elections (actual
outcomes, pre-election polls, and model estimates). With these estimated
uncertainties, we use Bayesian inference to integrate the various sources of
data to form posterior distributions for the state and national two-party
Democratic vote shares for the 2008 election. Our key idea is to separately
forecast the national popular vote shares and the relative positions of the
states.

The Applied Statistics Workshop meets each Wednesday at 12 noon in K-354
CGIS-Knafel (1737 Cambridge St).  The workshop begins with a light lunch and
presentations usually start around 1215 and last until about 130 pm.

Cheers,

Justin Grimmer
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