US elections
The history, mechanisms behind the Electoral College. A study of its possible effects on the allocation of campaign resources. Model that allows us to analyze the scope of the impact of the electoral college for the presidential campaigns in the US.
| Рубрика | Политология |
| Вид | дипломная работа |
| Язык | английский |
| Дата добавления | 31.05.2016 |
| Размер файла | 328,2 K |
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However, what removing fundraiser visits from the equation has done is raise the number of states which recorded zero visits by either campaign to 18. As such, again using logit regression, we can test the significance of the claim that an increased closeness of the state race leads to the state being more likely to receive non-fundraiser visits.
Table 4. Coefficients estimates with heteroskedasticity-consistent errors, non-fundraiser visits per million voters as dependent variable
|
Model 1 |
Model 2 |
Model 3 |
Model 4 |
||
|
Constant |
8.309* |
-7.220 |
8.651** |
0.100 |
|
|
(4.202) |
(25.639) |
(4.242) |
(19.119) |
||
|
GDP_PC |
0.000 |
0.000 |
0.000 |
0.000 |
|
|
(0.000) |
(0.000) |
(0.000) |
(0.000) |
||
|
Donations_PC |
0.734 |
0.887 |
0.853 |
0.838 |
|
|
(0.680) |
(0.956) |
(0.663) |
(0.799) |
||
|
Poll Margin |
-0.370** |
-0.350** |
|||
|
(0.149) |
(0.167) |
||||
|
Previous Years |
-0.493*** |
-0.490** |
|||
|
(0.167) |
(0.181) |
||||
|
Undecided |
-0.384 |
-0.386 |
|||
|
(0.605) |
(0.390) |
||||
|
Mod |
0.346 |
0.111 |
|||
|
(0.869) |
(0.634) |
||||
|
Electoral Votes per 10^6 |
1.557 |
0.659 |
2.001 |
1.522 |
|
|
(2.417) |
(2.021) |
(1.318) |
(1.479) |
||
|
R-squared |
0.210 |
0.209 |
0.295 |
0.285 |
|
|
N of Observations |
45 |
45 |
48 |
48 |
Using our four different sets of dependent variables, we find that all of them perform worse in predicting these particular outcomes - with prediction percentages lower for every model in this logit calculation than in the preceding ones which dealt with ad money.
Base analysis suggests that the relationship between measures of competitiveness and the likelihood of a state receiving non-fundraiser visits is statistically significant for the 2012 election, as both indicators were given significant coefficients in either specification of the model. None of the other included variables were statistically significant predictors of the probability of non-fundraiser visits except for the share of undecided voters, which received a significant coefficient in model 3.
Table 5. Coefficient estimators for logit regression analysis with presence of non-fundraiser visits as dependent variable
|
Model 1 |
Model 2 |
Model 3 |
Model 4 |
|||
|
Constant |
7.904 |
-2.012 |
8.807** |
-1.015 |
||
|
4.928 |
(6.373) |
(4.449) |
(5.099) |
|||
|
GDP_PC |
0.000 |
0.000 |
0.000* |
0.000 |
||
|
(0.000) |
(0.000) |
(0.000) |
(0.000) |
|||
|
Donations_PC |
0.000 |
0.000 |
0.000 |
0.000 |
||
|
(0.000) |
(0.000) |
(0.000) |
(0.000) |
|||
|
Poll Margin |
-0.096* |
-0.076* |
||||
|
(0.054) |
(0.046) |
|||||
|
Previous Years |
-0.127** |
-0.088* |
||||
|
(0.064) |
(0.052) |
|||||
|
Undecided |
-0.615* |
-0.756** |
||||
|
(0.329) |
(0.306) |
|||||
|
Mod |
0.087 |
0.006 |
||||
|
(0.196) |
(0.155) |
|||||
|
Electoral Votes per 10^6 |
0.522 |
-0.311 |
1.004 |
0.260 |
||
|
(0.785) |
(0.291) |
(0.636) |
('0.464) |
|||
|
Chi-Square |
21.528 |
16.986 |
24.909 |
15.482 |
||
|
0.001 |
0.005 |
0.000 |
0.008 |
|||
|
Hosmer and Lemeshow |
2.181 |
9.081 |
4.388 |
4.851 |
||
|
0.949 |
0.247 |
0.821 |
0.773 |
|||
|
Cox & Snell |
0.380 |
0.314 |
0.405 |
0.276 |
||
|
Nagelkerke |
0.518 |
0.428 |
0.552 |
0.376 |
||
|
Percentage Correct |
80 |
82.2 |
79.2 |
75 |
||
|
N of Observations |
45.000 |
45 |
48 |
48 |
||
|
Bootstrap Confidence Intervals for Coefficients |
||||||
|
Constant |
Low |
-1.332 |
-29.153 |
3.590 |
-19.314 |
|
|
Upp |
7.880 |
7.852 |
26.594 |
8.422 |
||
|
GDP_PC |
Low |
-0.000 |
-0.000 |
-0.000 |
-0.000 |
|
|
Upp |
0.000 |
0.000 |
0.000 |
0.000 |
||
|
Donations_PC |
Low |
-0.000 |
-0.000 |
-0.000 |
-0.000 |
|
|
Upp |
0.000 |
0.000 |
0.000 |
0.000 |
||
|
Poll Margin |
Low |
-20.518 |
-0.333 |
|||
|
Upp |
-0.001 |
0.005 |
||||
|
Previous Years |
Low |
-0.520 |
-0.273 |
|||
|
Upp |
-0.041 |
-0.014 |
||||
|
Undecided |
Low |
-22.727 |
-2.410 |
|||
|
Upp |
0.217 |
-0.414 |
||||
|
Mod |
Low |
-0.263 |
-0.315 |
|||
|
Upp |
0.934 |
0.624 |
||||
|
EV_M |
Low |
2.119 |
-2.438 |
0.013 |
1.167 |
|
|
Upp |
289.160 |
1.196 |
4.651 |
1.639 |
It is worth noting, however, that the coefficient for the margin projected by polls was only significant on the 90% confidence level, as was the measure for previous years in model 4. The measure in model 3 was the only one to crack 95%. The bootstrapping of the values seems to confirm that as the confidence interval for the polls measure in model 2 outright overlaps with zero, placing the validity of the relationship under question (Table 5).
The sum total, the conclusion of all of this is that the nature behind the strategies of campaign visits isn't entirely clear cut. While the probability of there being a fight for the states' electoral votes is definitely a factor, as shown by the results of the regression analysis adjusted robust standard errors, it might not be the only factor. The logit models suggest that sheer projection of competitiveness isn't the end all-be all of determining the likelihood of a state receiving visits, even we account for the specific procedure of fundraising.
Looking at the individual data seems to confirm this claim - certain states that were visited by the campaigns were never going to be in play. For instance, Wyoming, Texas, Louisiana, Utah were all visited by various campaign officials as part of non-fundraising campaigning - in some of them, there were important Senate or House reasons to speak of, while, in others, one has to assume other highly specific reasons - for instance, appearing at events of big lobbying groups (like, for instance, the NAACP in Texas) in order to gain their support.
However, for those states that did appear to be closely contested, the pattern seen in advertising money held true - New Hampshire was, again, easily the most disproportionately favored state at 34 non-fundraising visits per million resident voters, while Florida received just 6, despite being frequently considered the most closely contested state election after election.
Table 6. Coefficients for logit regression on separate data for two major parties
|
Democrat Campaign Data |
Republican Campaign Data |
|||||||||
|
Model 1 |
Model 2 |
Model 3 |
Model 4 |
Model 1 |
Model 2 |
Model 3 |
Model 4 |
|||
|
Constant |
16.889* |
-19.590 |
54.925 |
-17.097 |
3.101 |
-28.154** |
1.782 |
-18.107 |
||
|
(9.279) |
(13.028) |
(38.474) |
(19.409) |
(4.363) |
(13.921) |
(5.286) |
(11.857) |
|||
|
GDP_PC |
0.000 |
0.000 |
0.000 |
0.000 |
0.000 |
0.000 |
0.000 |
0.000 |
||
|
(0.000) |
(0.000) |
(0.000) |
(0.000) |
(0.000) |
(0.000) |
(0.000) |
(0.000) |
|||
|
Party_Donations_PC |
0.700 |
0.778 |
-1.664 |
0.346 |
-0.146 |
-0.617 |
-0.818 |
-0.784 |
||
|
(0.800) |
(0.730) |
(2.254) |
(1.232) |
(0.799) |
(0.875) |
(1.624) |
(1.721) |
|||
|
Poll Margin |
-0.565** |
-0.491*** |
-0.337*** |
-0.434*** |
||||||
|
(0.229) |
(0.187) |
(0.116) |
(0.155) |
|||||||
|
Previous Years |
-1.369* |
-0.723*** |
-0.627*** |
-0.659*** |
||||||
|
(0.744) |
(0.273) |
(0.236) |
(0.228) |
|||||||
|
Undecided |
-1.034** |
-3.177 |
-0.274 |
-0.100 |
||||||
|
(0.520) |
(2.215) |
(0.301) |
(0.369) |
|||||||
|
Mod |
0.534 |
0.514 |
0.820* |
0.538 |
||||||
|
(0.346) |
(0.526) |
(0.423) |
(0.334) |
|||||||
|
Electoral Votes per 10^6 |
0.358 |
0.652 |
2.198 |
1.070 |
1.240 |
0.990 |
2.059** |
1.874* |
||
|
(0.999) |
(0.937) |
(2.477) |
(1.548) |
(0.755) |
(0.749) |
(0.997) |
(0.996) |
|||
|
Chi-Square |
28.884 |
25.789 |
43.625 |
37.068 |
22.774 |
28.344 |
34.627 |
37.574 |
||
|
0.000 |
0.000 |
0.000 |
0.000 |
0.000 |
0.000 |
0.000 |
0.000 |
|||
|
Hosmer and Lemeshow |
6.015 |
2.351 |
0.374 |
1.792 |
3.539 |
7.167 |
4.093 |
5.187 |
||
|
0.538 |
0.938 |
1.000 |
0.987 |
0.831 |
0.412 |
0.849 |
0.737 |
|||
|
Cox & Snell |
0.474 |
0.436 |
0.597 |
0.538 |
0.397 |
0.467 |
0.514 |
0.543 |
||
|
Nagelkerke |
0.706 |
0.650 |
0.906 |
0.816 |
0.559 |
0.658 |
0.733 |
0.774 |
||
|
Percentage Correct |
91.1 |
88.9 |
95.8 |
96 |
86.7 |
86.7 |
93.8 |
91.7 |
||
|
N of Observations |
45 |
45 |
48 |
48 |
45 |
45 |
48 |
48 |
Up to this point, we have viewed the two competing parties and candidates as largely interchangeable, assuming that their strategies largely mirrored each other in every given state. However, we do need to account for potential deviations and, as such, it is necessary to perform some party-specific calculations.
To test the validity of our claim, we will again turn to logistic regression to see whether the relationship between the probabilities of targeted ad spending and perceived election closeness. For both parties in question, the binary variable for significant ad spending will be created at a cutoff point that is half that of the original combined calculations. As such, for Republicans, the same 14 states as in the combined models will be flagged as having received significant advertising - for Democrats, meanwhile, the amount of ad-affected states is down to 11.
The analysis shows that the explanatory variables perform well for both Republican and Democrat campaign data when it comes to ad spending, with the impact of our variables being flagged as significant in all eight cases, albeit to varying degrees of actual statistical significance. The models perform marginally better on Republicans than on Democrats (which is perhaps explained by the Democrats' reluctance to campaign in states that narrowly leaned red) but the difference is largely negligible (Table 6). We have also run the logit regression on the presence on non-fundraiser visits, where the results were rather expectedly varied. For the data on the Democrats' campaign, different measures of closeness were the only reliably significant predictor of probability. For Republicans, it was, surprisingly, donations that were a better predictor.
Maine and Nebraska
In the 2008 election, Republican candidate John McCain won the popular vote in Nebraska by 14 percent, while Democrat Barack Obama won in Maine by 17 percent. It is safe to assume, therefore, that neither state would receive much attention in 2012 if the electoral votes were allocated on a winner-take-all basis.
We have previously mentioned that that is not the case - both states award part of their electoral votes for winning the popular vote and part for winning in individual congressional district. But has that specific trait earned either state more campaign attention?
The data on visits does not seem to confirm the theory - neither campaign was at all present in Maine throughout the run-up to the election, while Nebraska saw one visit - a fundraising appearance by Ann Romney.
The ad spending, however, paints a different picture - while Maine, with its both congressional districts leaning Democrat, received a few hundred thousand dollars in spending, the count for Nebraska was into millions - two from the Obama camp and four from the Romney campaign.
Most importantly, all of the ad spending in Nebraska was concentrated in the second Congressional district, which was carried by Obama in 2008 by one percent. The other districts, which were expected to safely lean Republican, didn't receive ad spending.
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