Multivariate Results: The Governor's Race
The multivariate analysis is comprised of a series of logit models, one for each party-contest combination.[20] Table 5.4 presents the results for the gubernatorial race. The logit model for Republican crossover voting in the first column confirms several of our expectations. For one, the coefficient for liberalism is statistically significant and positive. As Republicans became more liberal, the probability of a crossover vote increased. Furthermore, the coefficient for strength of partisanship is negative and statistically significant, indicating that increased partisanship was associated with a declining probability of crossing over. The coefficient for gender is also significant and positive; other things equal, Republican women were more likely than their male counterparts to cross over in the gubernatorial race. By contrast, income is negatively associated with a crossover vote. The wealthier the Republican voter, the less likely he or she was to vote for a Democrat in the primary. Votes for both Prop 226 and Prop 227 are
| Republicans | Democrats | |||
|---|---|---|---|---|
| Coefficient | Probability | Coefficient | Probability | |
| SOURCE: Field Institute, Field Polls (San Francisco: The Field Institute, 1998). NOTE: Table entries are logit coefficients, with standard errors in parentheses. The dependent variable is coded 1 for a crossover vote and 0 otherwise. The rate of Republican crossover was 27.8 percent, and the rate of Democratic crossover was 7.1 percent. Change in probability is the change in the probability of crossover voting associated with a shift from the minimum to the maximum value of the independent variable, holding all other variables at their mean values. *p < .05 **p < .01 ***p < .0001 | ||||
| Liberalism | 0.18* | .27 | −0.27** | −.07 |
| (0.07) | (0.11) | |||
| Strength of partisanship | −0.63*** | −.30 | −0.14 | |
| (0.14) | (0.20) | |||
| Prop 226 vote | −0.32 | 1.03** | .05 | |
| (0.22) | (0.34) | |||
| Prop 227 vote | −0.12 | 0.14 | ||
| (0.25) | (0.34) | |||
| Gender | 0.41* | .10 | −0.34 | |
| (0.20) | (0.31) | |||
| Protestant | −0.19 | −0.44 | ||
| (0.23) | (0.38) | |||
| Catholic | −0.06 | −0.24 | ||
| (0.27) | (0.39) | |||
| Income | −0.22** | −.18 | 0.23* | .04 |
| (0.08) | (0.12) | |||
| Age | −0.005 | 0.008 | ||
| (0.006) | (0.01) | |||
| Education | −0.04 | −0.16* | −.07 | |
| (0.05) | (0.08) | |||
| Black | — | −0.59 | ||
| (0.56) | ||||
| Latino | — | −0.79 | ||
| (0.54) | ||||
| Union member | — | 0.66* | .03 | |
| (0.31) | ||||
| Constant | 1.98** | −1.55 | ||
| (0.73) | (1.11) | |||
| −2 x log-likelihood | 664.3 | 339.6 | ||
| Percentage correctly predicted | 74.6 | 92.9 | ||
| No crossover | 94.9 | 100.0 | ||
| Crossover | 21.8 | 0.0 | ||
| Pseudo-R 2 | .11 | .11 | ||
| N | 627 | 743 | ||
Table 5.4 also presents the change in the predicted probability of crossing over associated with a shift from the minimum to the maximum value of the statistically significant variables. The results for Republican crossover voting demonstrate the power of partisanship and ideology. With all other variables held at their means, the probability that a strong liberal Republican crossed over was .27 greater than that of a strong conservative Republican. A comparable probability obtains for strength of partisanship. Income also had a strong effect: the highest income group is predicted to have a probability of crossing over .18 lower than that of the poorest group. Gender has a weaker effect.[21]
Comparable models of Democratic crossover for Governor, presented in column two of table 5.4, produce generally similar results. While liberalism has the hypothesized effect—the probability of crossing over declines with increasing liberalism—the strength of partisanship variable is insignificant. However, the Prop 226 vote is statistically significant. Support for Prop 226, which is in essence an anti-union vote, is associated with a higher probability of crossover voting among Democrats.
That gender is not significant in this or any model of Democratic crossover demonstrates that the "pull" effect of gender—its ability to keep Democrats within the party—is not as strong as its "push" effect—its ability to drive Republicans toward Democratic candidates. In other words, Democratic men are less likely to defect than Republican women are. Of the remaining demographic variables in this model, income, education, and union membership have significant effects. As income increases, the propensity to cross over among Democrats increases. Education has the opposite effect. As Democratic respondents become more educated, ceteris paribus, their propensity to cross over in the gubernatorial primary decreases. Curiously, the effect of union membership is in the opposite direction than expected: being a union member (or having one in the family) was associated with a greater likelihood to cross over and vote for Lungren. However, the associated change in predicted probability shows that this unanticipated effect was relatively weak.[22]