95
Table 7.3: Percentage of Former Governors that Won a Gubernatorial Race
after a Congressional Period
|
- : . |
r-~--□ | ||
|
⅛⅛√?' 'i- .~i∙¾ |
li≡iα ' |
≡≡li |
Total ∖ |
|
■ r∖ |
139 |
38 |
177 |
|
78.53 |
21.47 |
100.00 | |
|
20 |
1 |
2T | |
|
95.24 |
4.76 |
100.00 | |
|
• ∙ .’<Z fr⅛, ., |
159 |
39 |
198 |
|
80.3 |
19.70 |
1ÔÔ | |
Table 7.4: Percentage of Former Mayors that Won a Municipal Race after a
Congressional Period
|
■■ ■■ | |||
|
t , 0 |
1 ι |
Total | |
|
• ∙'γλ ■ ; ∙ , ∙ φ.∙ ∙. ∙ |
43 |
25 |
68 |
|
63.24 |
36.76 |
100.00 | |
|
, ’ . ’< I ∙ ∙ ‘ ,. |
26 |
3 |
29 |
|
89.66 |
10.34 |
100.00 | |
|
.- ■ ■■■■: '∙½i : ' |
69 |
28 |
97 |
|
71.13 |
28.87 |
ÏÔ0 | |
Overall, the specification of the models includes most of the covariates used in
previous chapters. I will analyze the effect of the number of locally and provincially
targeted bills on the chances of winning an executive race, controlling for previous
career background, distance to the majority party median position, distance to the floor
median position, district magnitude, committee chairmanship and membership to the
Peronist party. Additionally, I include a new pair of covariates that I judge appropriate
for the current models. One is whether the candidate belongs to the outgoing executive's