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Bandwagons and Kerry vs. Bush 2004
Unformatted Document Text:  13 [Insert Table 3 Here] Modeling across both education and categories of how close the respondents follow politics is even more insightful. The nine favorability models have been estimated on unweighted data using controls for gender, race, direction of party identification, and general media exposure to newspapers, cable television news and network news. In the model that includes the entire sample (all educational and attentiveness subgroups) the LAST POLL variable is significant at better than P<.01. Thus without digging any deeper it would appear that the previously released poll does indeed have an impact on how all voters evaluate the candidates. As these models are OLS estimates the coefficients are relatively easy to interpret. A single percentage change in the difference between the candidates in the last released poll would predict a change of .027 in net candidate favorability. Conceptualized another way, a 10 point poll shift would lead to almost 3/10ths of a point shift in favorability. That number may seem small, but by simply looking at Figure 3 it should seem clear that 3/10ths of a point would span almost half the total variance in the trend line. Almost half the variance in someone’s net favorability rating for the 2004 presidential candidates can be explained by the model (which granted contains does contain the “super attitude” party identification). When we look across categories for how often the respondent follows politics a number of things stand out. Firstly one is struck by the differences in the R-square values across the models (follows politics often: r^2 = .557, follows politics not often: r^2 = .344). 21% more variance in the net favorability score is explained in the model where someone often follows politics as opposed to the model where the respondents do not follow politics very often, all other control variables remaining the same. This would

Authors: Daigle, Delton.
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13
[Insert Table 3 Here]
Modeling across both education and categories of how close the respondents
follow politics is even more insightful. The nine favorability models have been estimated
on unweighted data using controls for gender, race, direction of party identification, and
general media exposure to newspapers, cable television news and network news. In the
model that includes the entire sample (all educational and attentiveness subgroups) the
LAST POLL variable is significant at better than P<.01. Thus without digging any deeper
it would appear that the previously released poll does indeed have an impact on how all
voters evaluate the candidates. As these models are OLS estimates the coefficients are
relatively easy to interpret. A single percentage change in the difference between the
candidates in the last released poll would predict a change of .027 in net candidate
favorability. Conceptualized another way, a 10 point poll shift would lead to almost
3/10ths of a point shift in favorability. That number may seem small, but by simply
looking at Figure 3 it should seem clear that 3/10ths of a point would span almost half the
total variance in the trend line. Almost half the variance in someone’s net favorability
rating for the 2004 presidential candidates can be explained by the model (which granted
contains does contain the “super attitude” party identification).
When we look across categories for how often the respondent follows politics a
number of things stand out. Firstly one is struck by the differences in the R-square values
across the models (follows politics often: r^2 = .557, follows politics not often: r^2 =
.344). 21% more variance in the net favorability score is explained in the model where
someone often follows politics as opposed to the model where the respondents do not
follow politics very often, all other control variables remaining the same. This would


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