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¬gure 3.2. Probability and Decentralization Interacted



do not change much, however, when I exclude Thailand (see Figures 3.2c
and 3.2d). The marginal effect of decentralization is still positive and
increasing in probability, though with Thailand excluded, this marginal
effect is no longer signi¬cant at high levels of probability.
Finally, the ¬nal two graphs in Figures 3.2e and 3.2f show the
marginal effect of probability as decentralization increases. Note that
where there is a high aggregation payoff (decentralization ¼ 0), the
marginal effect of probability on in¬‚ation is indistinguishable from zero.
In other words, a high aggregation payoff can be enough to induce
aggregation even if the probability of capturing that prize is low.
Building Party Systems in Developing Democracies
70

However, as the aggregation payoff declines, an increase in probability
is associated with a rise in party system in¬‚ation. This positive marginal
effect continues to increase as decentralization increases.
To summarize, the results of these models are consistent with both
the Prime Minister and Expected Utility hypotheses. In the additive
models, an increase in the probability that someone other than the
leader of the largest party will capture the premiership is associated
with greater in¬‚ation. (In those same models, the proxy for the
aggregation payoff “ decentralization “ is signi¬cantly positive, as
expected). The interactive models are consistent with my argument
that aggregation incentives are a re¬‚ection of both the size of
the aggregation payoff and the probability of capturing that
payoff. Decentralization, my measure of the aggregation payoff,
has its strongest marginal effect on in¬‚ation when combined with a
high likelihood of not capturing the premiership. In other words,
aggregation is the worst when there is both a low aggregation payoff
and a low probability of capturing that prize, as hypothesized.


3.5 the probability of capturing the
prize “ presidential systems
In presidential democracies, the probability that the largest legislative
party will also capture the presidency is a function of whether presi-
dential and legislative elections are concurrent and the effective number
of presidential candidates. The arguments about the probability of
capturing the prize of government in presidential systems can be
summarized with the following hypotheses.

Concurrency Hypothesis: In¬‚ation is lower when presidential and
legislative elections are concurrent.
ENPresxConcurrency Hypothesis 1: The effect of concurrent elections
on in¬‚ation is conditional on the effective number of presidential
candidates. As the effective number of candidates increases,
the negative relationship between concurrency and in¬‚ation
weakens.
ENPresxConcurrency Hypothesis 2: The effective number of presi-
dential candidates is positively related to in¬‚ation in concurrent
elections.
Testing the Theory 71

In Chapter 2, I also argued that a ban on reelection for the president
should increase the number of presidential candidates, ceteris paribus,
which suggests the following hypothesis.

Reelection Hypothesis: The effective number of presidential
candidates is positively correlated with restrictions on presiden-
tial reelection.

Data on the effective number of presidential candidates (ENPres) and
the concurrency of elections come from Golder (2005).28 To capture the
proximity of legislative and presidential elections, I use a dummy vari-
able that equals 1 if presidential and legislative elections are held in the
same year, 0 if they are not.29 For restrictions on presidential reelection, I
use a variable coded as 1 if the sitting president is not eligible for
reelection (no_reelection). This operationalization is preferable to a
simple dummy variable for whether or not a country places term limits
on a president. Coding the variable for term limits lumps together
countries where presidents face a single term limit (e.g., Mexico or the
Philippines) with countries that allow presidents to serve multiple but
limited terms (e.g., the United States). Since what I ultimately care about
is whether in any given presidential election there is an incumbent
running, no_reelection seems like the logical choice.30 No_reelection is
calculated from data in the DPI (Beck et al. 2001).
I test these hypotheses using both cross-sectional and pooled models.
I again use OLS with robust standard errors clustered by country for the
pooled analyses for the reasons described previously. To test
the hypotheses, I use three different datasets. The ¬rst is a subset of the
dataset described in the previous sections and consists of 81 elections in
18 presidential democracies. I use this dataset to directly test the
hypotheses relating aggregation to concurrency, the effective number
of presidential candidates, and the interaction of these two variables.
Given that this ¬rst dataset is small I also indirectly test the same
three hypotheses using Golder™s legislative elections dataset (2005).

28
The effective number of presidential candidates is calculated by dividing 1 by the sum
of each candidate™s squared vote share: 1/Rvi2.
29
The results are robust to the substitution of a continuous variable measuring the
distance between presidential and midterm elections on a 0 to 1 scale.
30
Even better would be data on whether the incumbent actually runs. Unfortunately
such data have not been gathered in a single dataset to my knowledge.
Building Party Systems in Developing Democracies
72

This dataset covers all democratic legislative elections in the world
from 1946 to 2000 for a total of 784 elections.31 The dependent
variable from this dataset is the effective number of electoral parties at
the national level (ENPnat). Ceteris paribus the effective number of
legislative parties is positively correlated with the in¬‚ation score.32
However, unlike in¬‚ation, ENPnat does not distinguish between the
degree of aggregation across districts and the amount of coordination
within those districts. To control for the district-level effects, I include
the log of average district magnitude (log_avemag) and ethnic frac-
tionalization (ef). We know that these two variables interact to
determine the effective number of parties at the district level (Cox
1997). The district magnitude data come from Golder (2005) and the
ethnic fractionalization data are from Fearon (2003) as described
previously.
To test the reelection hypothesis I use a third data set “ Golder™s
presidential elections dataset. This dataset includes 294 democratic
presidential elections from 1946 to 2000. I focus only on direct election
in presidential democracies and so exclude from my models elections in
hybrid presidential-parliamentary regimes as well as any cases of
indirect presidential elections (e.g., the United States).33 This brings the
number of observations in the dataset to 170. The dependent variable
from this dataset is the effective number of presidential candidates
(ENPres). The main explanatory variable is the presence (or absence)
of a ban on reelection of the sitting president (no_reelection).
As discussed in Chapter 2, the effective number of presidential
candidates (like the effective number of parties) is a product of an
interaction between electoral rules and social structure (Golder 2006).
Ethnic heterogeneity increases the effective number of presidential
candidates only when accompanied by a permissive electoral formula
(namely, majority runoff). I replicate this ¬nding and then add the

31
The total dataset includes 867 elections. This excludes Columbian elections from
1958 to 1970 when there was an agreement between Columbia™s two major parties to
alternate control of government and the share of legislative seats regardless of elec-
toral results. Another 76 elections are dropped from the sample due to a lack of party
vote share data, which are needed to calculate the effective number of electoral
parties.
32
Speci¬cally, holding the average number of parties at the district level constant.
33
Leaving indirect presidential elections in the dataset does not substantively alter the
results.
Testing the Theory 73

no_reelection variable to see whether it has a signi¬cant independent
effect on the effective number of presidential candidates. Ethnic
heterogeneity is measured, as it has been previously, as the ethnic
fractionalization (ef). Runoff is a dummy variable coded 1 if the
presidential election formula is a runoff, 0 otherwise.


3.5.1 Results

Table 3.6 displays the results using my in¬‚ation dataset and Golder™s
legislative elections dataset. In columns 1, 4, and 5, the dependent vari-
able is in¬‚ation. The effective number of electoral parties (ENPnat) is the
dependent variable in columns 2, 3, 6, and 7. Looking ¬rst at the results
from the in¬‚ation models, we can see that, as expected, party system
in¬‚ation is lower where presidential and legislative elections are con-
current “ proximity has a signi¬cant negative effect when ENPres is 0.
Also in line with the ¬rst interaction hypothesis, the de¬‚ationary effect of
concurrent elections diminishes as the effective number of presidential
candidates rises. The coef¬cient on the interaction term proximity*
ENPres is positive and signi¬cant in all of the model speci¬cations. This
relationship holds even when controlling for the size of the aggregation
payoff as in model 5. (Note that decentralization is still positive and
signi¬cant in model 5, even when controlling for the number of presi-
dential candidates and proximity).
The story is similar if we substitute the effective number of electoral
parties (ENPnat) for in¬‚ation as the dependent variable in models 2, 3, 6,
and 7. Models 2 and 6 use my dataset. For a robustness check, I also run
the same speci¬cations using Golder™s larger legislative elections dataset
(models 3 and 7). The substantive results are the same regardless of
which dataset I use. With ENPnat as the dependent variable, my analyses
are similar to recent studies on the effect of presidential election on
legislative fragmentation (Cox 1997; Mozaffar et al. 2003;
Golder 2006). The ¬ndings are consistent with these existing studies.34
Proximity reduces the effective number of electoral parties (proximity is
negative and signi¬cant in all four speci¬cations), but this effect is
conditional on the effective number of presidential candidates. An
increase in the number of candidates undermines the marginal negative

34
See especially Golder (2006, 11“13).
74
table 3.6. Aggregation in Presidential Democracies

Cross-Sectional Analyses “ Dependent Variable Pooled Analyses “ Dependent Variable

Explanatory 1 2 3 (ENPnat) 7 (ENPnat)
Variables (in¬‚ation) (ENPnat) (Golder) (Golder)
4 (in¬‚ation) 5 (in¬‚ation) 6 (ENPnat)
proximity À0.68*** À6.95*** À5.02*** À0.43*** À0.19** À4.30** À3.43***
(0.04) (1.66) (1.66) (0.10) (0.06) (1.57) (1.26)
1.32** 0.61*
ENPres À0.04** À0.14 À0.04 À0.04* À0.04
(0.01) (0.61) (0.60) (0.03) (0.02) (0.39) (0.36)
0.18*** 1.81** 0.28 0.13*** 0.08*** 1.31** 0.65*
proximity*ENPres
(0.02) (0.72) (0.86) (0.03) (0.02) (0.51) (0.37)
0.11 0.74 1.84 0.19 0.49** 2.43**
ef À0.67
(0.07) (2.73) (1.57) (0.11) (0.16) (1.52) (1.16)
log_govage À0.02* À0.05*** À0.09***
(0.01) (0.01) (0.02)
log_districts À0.01 À0.001 À0.03*
(0.01) (0.01) (0.02)
0.69 0.75 0.81*
log_avemag À0.09
(1.09) (0.60) (0.70) (0.41)
0.73 2.56
ef*avemag À0.46 À0.34
(2.12) (0.89) (1.98) (0.83)
0.13**
decentralization
(0.04)
0.44*** 3.65* 2.04 0.42*** 0.31*** 3.19** 1.39
Constant
(0.06) (1.82) (1.40) (0.10) (0.09) (1.42) (1.31)
0.95 0.80
R-squared .56 .63 .77 .64 .39
15 16 26 61 45 74 182
Observations
* p < .1, ** p < .05, *** p < .01; standard errors in parentheses
Testing the Theory 75

effect of proximity on the number of parties (the interaction term,
proximity*ENPres, is positive in all four speci¬cations, signi¬cantly
so in three).
In Figure 3.3, I display the marginal effect graphs for four of the
seven models in Table 3.6, speci¬cally models 1, 2, 4, and 6.35 The
graphs tell a remarkably consistent story. Concurrent presidential
elections are associated with better aggregation (fewer parties and less
in¬‚ation), but only where there is a small effective number of presi-
dential candidates. Once the number of candidates rises to somewhere
between 2.5 and 3.5, the marginal effect of concurrency disappears
altogether. Focusing for a moment on just in¬‚ation (Figures 3.3a and
3.3c), we see that once the effective number of candidates is suf¬ciently
large, concurrent elections are actually associated with a signi¬cant
increase in in¬‚ation.
Table 3.7 presents the remainder of the presidential election models.
In the ¬rst cross-sectional speci¬cation and models 4 and 5 in the pooled
speci¬cations, I isolate the impact of the effective number of presidential
candidates on in¬‚ation and the number of parties when elections are
concurrent (proximity ¼ 1).36 We can see that when presidential and
legislative elections are concurrent, the effective number of presidential
candidates is positively related to both party system in¬‚ation and the
effective number of electoral parties, as hypothesized. If the effective
number of candidates is in fact so important for shaping aggregation
incentives, as it appears to be, then what determines the effective number
of candidates?
In models 2 and 6, the effective number of candidates (ENPres) is
the dependent variable, and I test whether reelection restrictions lead to
more presidential candidates, controlling for the strength of the elec-
toral system and social heterogeneity. The results provide some support
for the hypothesis that restrictions on reelection are associated with
more presidential candidates. In model 2, no_reelection is positive but
just short of signi¬cant, while in the pooled analysis (model 6) the
coef¬cient for no_reelection is both positive and signi¬cant. The lack of
an incumbent does appear to have an in¬‚ationary effect on the effective

35
The graphs for the other three models tell the same story.
36

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