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Electoral Consequences: The Importance of Political Parties in Brazil

Andrew Janusz

Seminar Paper

Date

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Voter participation in deciding electoral contests demonstrates voter beliefs that the type

of person who governs has consequences on outcomes. In majoritarian democracies, political

parties are considered to offer real choices to voters by nominating candidates for public office

(Lijphart 1984). By choosing among the slate of candidates put forth by political parties, voters

elect officials who then implement their preferred partisan policies (Lijphart 1984). At the

national and state levels, evidence shows that partisanship is a significant determinant of

economic, political, and social outcomes (Aldrich 1995; Bartels 2008; Besley and Case 2003;

Gerring 1998; Hacker and Pierson 2005; Lee, Moretti and Butler 2004; McCarty, Poole, and

Rosenthal 2006; Poole and Rosenthal 1997). Although local elections are by far the most

common type of election, significantly less research exists on the impact of partisanship on local

outcomes. In this paper I answer the following question: "what is the impact of mayoral

partisanship on local outcomes?"

I use non-parametric regression discontinuity designs to investigate how mayoral

partisanship impacts policy outcomes at the municipal level in Brazil's over 5,500 municipalities.

Brazil's federal structure grants party-affiliated mayors sole authority in primary education,

health care, and to some extent economic development, which thus makes it an excellent case to

explore the impact of partisanship on local outcomes. I find that municipalities that elect a

mayor of the center-left Workers' Party (PT), arguably Brazil's most cohesive and programmatic

political party, do not display better or worse education, health care or economic outcomes than

otherwise similar municipalities governed by a mayor of a different party. Moreover, when

political parties are grouped into ideological blocs using a variety of classifications, differences

in policy outcomes remain unforthcoming. These findings suggest that mayoral partisanship is

of little value in explaining local policy outcomes in Brazil.

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Literature Review

A rich literature exists on the relationship between ideology, partisanship and outcomes.

For both elected officials and voters, partisanship has emerged as an important determinate of

policy preferences. At the individual level, partisanship is a strong predictor of vote choice and

is used as a heuristic device for making voting decisions (Campbell et al. 1960; Goren 2005;

Green, Palmquist, and Schickler 2002; Popkin 1994; Schaffner, Streb, and Wright 2001).

Partisan differences between elected officials are thought to manifest themselves in

differences in policy outcomes, but this relationship has not been sufficiently explored at

different levels of federal systems. In the United States the distinct governing philosophies of

the Republican and Democratic parties explain differential policy outcomes well at the national

and state levels (Aldrich 1995; Bartels 2008; Gerring 1998; Hacker and Pierson 2005; Lee et al

2004; McCarty, Poole, and Rosenthal 2006; Poole and Rosenthal 1997). Significantly less

research has explored the impact of partisanship at the local level in the American context. Of

that body of work, findings have been mixed (Ferraz and Finan 2007; Ferreira and Gyorko 2009;

Gerber and Hopkins 2011). Gerber and Hopkins (2011) assert that these mixed findings are an

artifact of the outcomes studied. They contend that differential policy outcomes attributable to

partisanship are likely only to be found in those policy areas in which mayors exercise

significant political control. In the comparative context, a survey of the studies done on the

impact of partisanship on policy outcomes at the local level in federal systems yields mixed

findings (Furdas and Kis-Katos 2010; Pettersson-Lidbom 2008). This paper contributes to this

literature by identifying the causal impact of partisanship on local policy outcomes in Brazil.

The Brazilian Case

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Brazil's strong federal constitution, large number of municipalities and large number of

political parties make it an attractive case to explore the partisanship policy outcome puzzle. In

the majority of federal systems, most public policies are affected by politicians at multiple levels

of government. Brazil's federal constitution, in contrast, provides municipal level mayors most

legal, budgetary and administrative authority (Wampler 2004). Compared to politicians elected

to serve in the national legislature, sub-national government executives wield significantly more

power to hire, fire and to implement public works projects (Samuels 1998). In Brazil, mayors

are solely responsible for health care services, pre-school and primary education and even the

economy to some extent. In order to meet their responsibilities, Brazil’s democratic constitution

grants mayors the discretion to tailor programs to meet local constituent needs (Sugiyama 2008).

Brazil also has a large number of municipalities in which to identify the effects of

partisan on local policy outcomes. Politically, Brazil is composed of 26 states and a federal

district, with each state being composed of municipalities, akin to counties in the United States.

Each of Brazil's over 5,500 municipalities is governed by an elected mayor, who serves a four

year term with the option to run for one additional term.

Lastly, Brazil has a large number of active parties. Thirty-one parties are registered to

compete in elections. They do so with varying frequencies at the local, state and national levels.

While a candidate from each political party does not compete in every mayoral election, rarely

are mayoral races uncontested.

In order for differences in mayoral partisanship to affect municipal outcomes there must

be a strong association between party labels and policy positions. Although there is some doubt

that political parties in Brazil have ideological meaning (Lucas and Samuels 2010) conflict at the

national level between catch-all parties suggests otherwise (Coppedge 1997; Leoni 2002; Power

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and Zucco 2009; Saiegh 2009). Levels of party commitment in the Brazilian case are also

contested. Known for its weakly institutionalized party system, political parties in Brazil have

historically been volatile and uncohesive, with parties frequently breaking up, disappearing and

reemerging (Ames 2001; Power 2000). At the national level, in the Brazilian Chamber of

Deputies the open-list proportional representation format of elections is thought to candidates to

focus on their personal opinions and qualities as opposed to emphasizing their party affiliation or

the official party platform, leading to individualistic behavior (Ames 2001, 2002; Desposato

2006; Graeff 2000; Mainwaring 1991, 1997, 1999; Pinheiro Filho 1998). Faced with the

dilemma of whether to pursue their individual interests or to devote resources to maintaining

their party's collective reputation, Brazilian politicians have historically done the latter (Shugart

and Carey 1992). Because party has not been a strong indicator of the policies politicians will

support, Brazilians are thought to vote for personalities rather than parties or policies.

While other Brazilian political parties may lack ideological meaning, sanctioning

mechanisms within the PT have discouraged individualistic behavior and produced a nationally

recognizable party (Ames 2002; Hunter 2008; Mainwaring and Pérez-Liñan 1997; Samuels

2006). This has led some scholars to suggest that the PT is Brazil's most cohesive party

(Mainwaring 1999; Samuels 2006). In addition to being the most cohesive party, the PT party

platform prioritizes the poor and disadvantaged, resulting in a reputation of being an ally of the

underprivileged sectors of Brazilian society (Abers 1996; Pribble, Huber and Stephans 2009).

As a result of its cohesiveness and reputation, the PT has the strongest base of partisan identifiers

in the electorate (Samuels 2006).

At the national level, the PT gained acclaim in 2003 after its candidate, Luiz Inacio Lula

da Silva, won the presidency. Targeting social assistance funds to improve the lives of the

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poorest sectors of Brazilian society, under Lula's leadership, Bolsa Familia, the largest

conditional cash transfer program in Latin America, has directly benefitted over forty-four

million people (Hall 2008). Lula's legacy has been upheld by his successor, President Dilma

Rousseff, who has actively pursued a social policy agenda. Locally, the PT has also been

successful. Baiocchi (2003) writes that the cornerstone of the PT's success is due to

redistributive administrative schemes at the local level. Many PT administrations have decreased

or eliminated traditional forms of clientelism and corruption, ensuring that municipal funds are

appropriately spent on projects that improve the quality of life for municipal residents, such as

through construction of new schools or health clinics. In addition to education and health

projects, most PT administrations have incorporated greater citizen involvement and control in

small-scale municipal economic development projects (Abers 1996).

Though the PT may be Brazil's most cohesive political party, there is a disagreement in

the literature as to the relative cohesiveness of Brazilian political parties and thus the value of

partisanship. At the national level, some scholars suggest that levels of party discipline are

rising in other parties and they find that partisanship is an important determinant of legislative

behavior (Amorim Neto and Santos 2003; Figueiredo and Limongi 2000; Lyne 2005; Pereira and

Muller 2002). Increasing numbers of party oriented legislators may be leading Brazilian political

parties in the direction of developing credible, programmatically coherent platforms (Hagopian,

Gervasoni and Moraes 2009; Lyne 2005; Tafel 2011). Other scholars (Lucas and Samuels 2010)

reject the notion that Brazil's party system is becoming consolidated. Lucas and Samuels (2010),

for example, claim that few voters cast partisan votes due to their ignorance of party positions on

the issues. Lucas and Samuel's (2010) findings suggest that in the Brazilian context not only is

partisanship of little value but so is political ideology. They contend that while the PT is distinct,

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that no clear ideological differences exist between Brazil's other main political parties (Lucas and

Samuels 2010). Further, they suggest that the spatial distance between the PT and other parties is

diminishing (Lucas and Samuels 2010).

The ability to understand the relationship between partisanship and local outcomes is

essential to evaluating the value of political parties. Although a number of scholars have

examined political party behavior at the national level in a number of countries, including Brazil,

much less research has been done on the impact of political parties on local outcomes. In federal

systems, such as Brazil, a large portion of governance takes place at the state and local levels. As

a result, a comprehensive evaluation of Brazilian political parties requires an analysis of the

impact of partisanship on local outcomes. This paper will test whether the Brazilian political

parties do in fact exhibit cohesiveness at the local governance level.

Hypotheses

The debate explored above with respect to partisanship leads to the development of two

hypotheses. I contribute to the political partisanship and political ideology literatures by

empirically testing them.

Hypothesis 1: Municipalities governed by PT mayors display superior outcomes in the

areas of education, health care and the economy compared to similar municipalities

governed by mayors from another party.

Like PT representatives at the national level, I expect PT mayors to display programmatic

behavior. Because education, health care and the economy are of the utmost interest to the PT's

partisan voters, typically poor individuals who likely rely on public education for their children,

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and public health care for their families, PT mayors should display higher levels of commitment

to improving outcomes in these areas than mayors of other parties. The precarious economic

position of PT partisan voters should lead PT mayors to take steps to encourage economic

growth in the municipalities in which they govern.

Hypothesis 2: Municipal measures of education, health care and the economy should not

vary depending on the position of a mayor's political party on the left-right political

ideology spectrum.

If the assertions of Lucas and Samuels (2011) are correct differential outcomes between

otherwise similar municipalities on the basis of mayoral ideology will not be forthcoming.

Because they suggest that the spatial differences between the PT and other parties are shrinking

this includes municipalities governed by PT mayors.

To test these hypotheses, I estimate the causal effect of mayoral partisanship and political

ideology on measures of primary education, health care and the economy.

Methods

Estimating the causal effect of mayoral partisanship and political ideology on municipal

outcomes without bias presents a challenging identification problem. Mayoral partisanship and

by extension political ideology are not randomly assigned to municipalities, introducing the

possibility of endogeneity. Municipalities in which PT mayors tend to be elected are likely

different from municipalities governed by mayors from other parties both in observable and

unobservable ways. For example, a municipalities history of reelecting incumbent mayors may

be controlled for. Municipalities in which the top two rightist mayoral candidates coordinate and

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one of them exits the mayoral race to ensure that a leftist mayoral candidate does not win

however are different in unobservable ways from municipalities in which the top two rightist

candidates do not coordinate and split the rightist vote. Controls for observable differences can

be included in statistical models, but by definition unobservable differences cannot be controlled

for, leading to the possibility of biased estimates (Imbens and Lemieux 2008).

In light of these concerns, I test both of the previously states hypotheses using regression

discontinuity designs. A regression discontinuity design allows for comparison of municipalities

that are quite similar in their probability of receiving treatment, but differ in whether or not they

receive treatment. With regards to hypothesis 1, which concerns the causal effect of a PT mayor

on municipal outcomes, I rely on the intuition that municipalities in which PT mayoral

candidates were elected by narrow margins are a good counterfactuals for those municipalities in

which PT candidates lost their respective mayoral elections by narrow margins. I carry out a

similar process in order to attain the causal effect of political ideology on municipal outcomes. I

compare municipalities in which mayoral elections were decided by a small margin between

candidates of parties that have different ideologies. The regression discontinuities examine

elections of right versus candidates of left political parties, candidates of right versus candidates

of center political parties, and finally candidates of center versus candidates of left political

parties.

Candidates from several political parties compete in Brazilian municipal elections, with

the winning candidate being elected by plurality. For this reason, instead of using a fixed cutoff

of 50% like Green and Hopkins (2011) the margin of victory separating the elected mayor and

the first runner-up is instead used (Brambor and Ceneviva 2011; Imbens and Lemieux 2008). In

Brazilian municipalities with more than 200,000 eligible voters, mayors are directly elected

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through (run-off) majority rule. Because different electoral rules lead to different data generating

processes, municipalities with over 200,000 eligible voters are removed. Elections in which the

winning candidate and runner-up were of the same party or ideological bloc are removed in

respective regression discontinuities.

I treat the margin of victory between the winning candidate and the first runner-up as a

continuous variable. I limit my sample to include only municipalities in which treatment was

determined by a margin of victory of 3%. Increasing the margin of victory results in a larger

sample size and thus greater external validity, but at the cost of internal validity. As the margin

of victory increases additional observations are included, but the partisanship of the mayor is no

longer determined by a quasi-random variable. Additional models with varied margins of victory

can be found in the appendix. These models show the stability and strength of the causal

estimates.

Data

In order to determine treatment I use electoral data from the 2008 municipal elections

obtained from Brazil's Supreme Electoral Court (TSE). The TSE is responsible for managing all

elections in Brazil. This data set contains information about the partisan affiliation of candidates,

the number of votes they received and whether or not they were elected. Using 2004 municipal

electoral data I also generate a dummy variable for incumbency. As previously stated I removed

from this data set any municipality that resulted in a second round, runoff election

(municipalities with over 200,000 registered voters) as well as those in which the top two vote

receivers shared PT affiliation in the first set of regressions or ideological affiliation in the

following sets of regressions. See appendix ideological bloc classifications.

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The outcome variables used are obtained from FIRJAN (Federação das Indústrias do

Estado do Rio de Janeiro). FIRJAN produces yearly measures ranging from 0 to 1, with one

being better, for each municipality using official government statistics. Each of the dependent

variables used reflect municipal issues that mayoral candidates cite in their campaigns and that

they can affect through policy and programs. These include the economy, education and health

care. I used the 2010 FIRJAN measures, but include the respective measure from 2007 to

increase precision.

For the economy variable I use the FIRJAN measure of income and employment, which

is constructed from data available from the Ministry of Labour and Employment. This variable

gives equal weight (50% each) to both the number of formal jobs created and the average

monthly income of formal sector workers. One potential concern is that this does not reflect

informal sector job creation or income. Informal sector growth is likely uncorrelated with

mayoral partisanship and will therefore not bias the resulting estimates.

The FIRJAN measure of education is created from statistics available from the ministry

of education. It is designed to reflect both the supply and quality of early childhood education,

both of which are the responsibility of the municipality and thus overseen by the elected mayor.

The education variable is composed of measures for the early childhood education enrollment

rate, drop-out rate, ratio of students at the appropriate grade level by age, percent of teachers

with higher education, average amount of classroom instruction. Together these measures

provide a good measure of education access and quality.

Lastly, the FIRJAN measure of health care is created using statistics on the number of

pre-natal visits, preventable infant deaths and deaths from poorly defined causes. The infant

mortality rate is considered to be one of the best indicators of a municipality's health and

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therefore Brazil's health. Together the FIRJAN development index variables provide a good

indication of the quality of life in Brazil's municipalities.

Models

Four sets of three models each are presented below. I use economic well-being (labeled

as economic health), education and health care as the dependent variable for one model in each

set. For the first set of models I test the PT partisanship hypothesis using each dependent

variable. I test the political ideology hypothesis by comparing mayors from left versus center

parties in models 4-6, mayors from right versus center parties in models 7-9 and mayors from

right versus left parties in models 10-12.

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Table 1: PT Partisanship Regression ResultsVariable Model 1 Model 2 Model 3

Dependent Variable

Economic Health

Education Health Care

PT Mayor -0.0011 0.007 -0.0048

(0.0158) (0.007) (0.0076)

Incumbent 0.0293 -0.0193 0.0119

(0.0452) (0.0203) (0.0222)

2007 Economic Health

0.7157***

(0.0519)

2007 Education

0.9429***

(0.003)

2007 Health Care 0.7615***

(0.0313)

Constant 0.1057*** 0.0879*** 0.2151***(0.0231) (0.0208) (0.0239)

R-Squared 0.5519 0.8648 0.7983

N 160 160 160

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Table 2: Left vs Center Ideology Regression ResultsVariable Model 4 Model 5 Model 6

Dependent Variable

Economic Health


Leftist Party .0089 0.0105 0.0063

(0.0158) (0.0064) (0.0087)

Incumbent -0.0099 -0.0061 0.0230

(0.0513) (0.0218) (0.0296)


0.7027***

(0.0517)

2007 Education

0.8574***

(0.0273)

2007 Health Care 0.7546***

(0.0386)

Constant 0.1173*** 0.1428*** 0.2167***(0.0226) (0.0193) (0.0299)

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R-Squared 0.5125 0.8494 0.6930

N 182 182 182

Table 3: Center vs Right Ideology Regression ResultsVariable Model 7 Model 8 Model 9

Dependent Variable

Economic Health


Centrist Party 0.0302* 0.0060 0.0138*

(0.0156) (0.0063) (0.0079)

Incumbent -.0215 -0.0018 0.0438**

(0.0420) (0.0173) (0.0216)


0.7116***

(0.0550)

2007 Educatio

0.8751***

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n(0.0262)

2007 Health Care 0.7239***

(0.0337)

Constant 0.1000*** 0.1366*** 0.2458***(0.0240) (0.0184) (0.0264)

R-Squared 0.4370 0.8360 0.6870

N 232 232 232

Table 4: Left vs Right Ideology Regression ResultsVariable Model 10 Model 11 Model 12

Dependent Variable

Economic Health


Leftist Mayor -0.0088 -0.001 0.0048

(0.0146) (0.0066) (0.0078)

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Incumbent 0.0494 -0.0045 0.0019

(0.0452) (0.0205) (0.0247)


0.6449***

(0.0530)

2007 Education

0.9186***

(0.0294)

2007 Health Care 0.7403***

(0.0338)

Constant 0.1355*** 0.1063*** 0.2254***(0.0222) (0.0202) (0.0255)

R-Squared 0.4527 0.8432 0.7310

N 187 187 187

The results of models 1-3 are robust when the margin of victory is altered. Neither the

variable for PT mayoral partisanship nor incumbency is significant for elections decided by

margins of victory anywhere from one percent to ten percent. Graphs 1-6 in the appendix show

this visually. Similarly, in models 4-6 the results are robust for different margins of victory.

For model 7 when the margin of victory is altered to 4%, 5%, 9% and 10%, the Rightist

variable retains significance. This suggests that mayors from centrist parties are more successful

at increasing job growth and income, but because the relationship is not robust to all margins of

victory, this is not certain. Model 8 suggests that the presence of a rightist or centrist mayor does

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not result in significantly different education outcomes. When the same regression equation is

used but the margin of victory is 6%, 7%, and 10%, the rightist party variable does appear

significant. For model 9 the rightist party variable is only significant for the 3% margin of

victory suggesting electing a mayor of a centrist or rightist political party makes no difference.

Incumbency, however, is significant in all models suggesting that incumbents lead to better

health care outcomes if the incumbent mayors are from right or center political parties. Given

that incumbency is unimportant for the other dependent variables and in models that limit

elections to left and right parties or left and center parties incumbency is unconvincing. Lastly,

the results of models 10-12 are robust for different margins of victory.

The results of the above models support and extend the claims of Lucas and Samuels

(2010). While the PT is seen by many scholars as distinct from other political parties, at the

local level measures of the economy, education and health care suggest that PT affiliated mayors

are no better or worse than mayors from other political parties. One possible explanation is that

PT legislators are distinct at the national level but not at the municipal level. Another potential

explanation for this null finding is that the innovative municipal policies that PT mayors have

received credit for in the past decade have been adopted by mayors of other parties. A third

possibility is that PT mayors really are no better than mayors of other political parties at effecting

positive municipal change. Though the null is not rejected, mayoral partisanship in general and

PT partisanship specifically may still have causal effects. Policy outcomes are only one way to

explore potential effects of mayoral partisanship. Future studies should explore other

relationships, such as if mayoral partisanship affects clientelism and corruption.

Grouping political parties into ideological blocs also appears to be of little value. Quality

of life indicators are not statistically different when the mayoral candidate elected is affiliated

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with a party of the ideological left as opposed to right or center. Similarly electing a mayoral

candidate from a rightist party as opposed to a candidate from a centrist party does not result in

statistically significant quality of life outcomes.

Collectively these results suggest that mayoral partisanship and national ideology of

political parties at the local level are unimportant. Voters should vote for personalities, because

candidate partisanship does not appear to be of value. Even electing a member of the PT, which

is thought to be differentiable from other parties, does not differentially affect the quality of life

for municipal residents.

Appendix:

Table 1: Descriptive Statistics of all MunicipalitiesVariable Min Max Mean Std. Dev.

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Municipal Population 2007 804 10900000 32662.4 195220Municipal Population 2010 805 11300000 33859.7 200394Total Votes Cast in Each Municipality 718 1183720 15009.3 39623Number of Votes Received by Runner-up 1 295921 5155.57 10908.1Number of Votes Received by Winner 448 778514 8231.59 24225.1Winner's Vote Share 0.5 0.9998065 0.58514 0.08506Runner up's Vote Share 0.0001935 0.5 0.41486 0.08506Vote share of the PT candidate 0.0131449 0.9690194 0.48615 0.12627Winning Candidate is the Incumbent 0 1 0.02696 0.16199Winning Party is the Incumbent Party 0 1 0.28307 0.45053Incumbent Party is the PT 0 1 0.03936 0.19447Percent of Residents Receiving Aid 2007 0.0007231 0.2551578 0.08769 0.04578Percent of Residents Receiving Aid 2010 0.0003745 0.2383144 0.09465 0.04948Economic Health 2007 0.0445617 0.9853157 0.39846 0.1524Economy Health 2010 0 1 0.40431 0.15589Education 2007 0.3337345 0.9930894 0.68772 0.11569Education 2010 0.3746 1 0.74135 0.11261Health Care 2007 0.3410417 1 0.76274 0.11641Health Care 2010 0.4421 1 0.79855 0.10047

Table 2: Descriptive Statistics of Municipalities in the 3% SampleVariable Min Max Mean Std. Dev.Municipal Population 2007 966 307284 18431.2 28232.9

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Municipal Population 2010 1020 300466 19370.4 29585.3Total Votes Cast in Each Municipality 878 151338 10896.1 14673.7Number of Votes Received by Runner-up 428 48601 4700.07 5728.16Number of Votes Received by Winner 448 50710 4847.53 5922.06Winner's Vote Share 0.5 0.5149878 0.50766 0.00438

Runner up's Vote Share0.485012

2 0.5 0.49234 0.00438

Vote share of the PT candidate0.485282

5 0.5149527 0.50006 0.00821Winning Candidate is the Incumbent 0 1 0.02514 0.15666Winning Party is the Incumbent Party 0 1 0.25698 0.43728Incumbent Party is the PT 0 1 0.03352 0.18011

Percent of Residents Receiving Aid 20070.002140

6 0.222907 0.08983 0.04553

Percent of Residents Receiving Aid 20100.004207

5 0.2383144 0.09778 0.05001

Economic Health 20070.052208

7 0.9706729 0.3888 0.14383Economy Health 2010 0 0.9438 0.39228 0.14521

Education 20070.362240

3 0.9888889 0.68068 0.1139Education 2010 0.437 1 0.73164 0.11118

Health Care 20070.403943

3 1 0.76023 0.11736Health Care 2010 0.4665 1 0.79304 0.10341

Table 3: Categorization of Political Parties by IdeologyIdeology Parties Left PDT, PC doB, PSB, PSDC, PT, PRTB, PTBCenter PMDB, PMN, PPS, PSDB, PHS, PSDB

RightDEM, PT do B, PP, PR, PRB, PV, PTN, PTC, PRP, PSC, PSL, PTB, PSDC

Table 4: Ideology ObservationsVariable Full Sample 3% SampleLeftist Defeated Centrist 1385 186Centrist Defeated Rightist 1698 237Leftist Defeated Rightist 1302 190

Janusz 22

Graph 1: Scatter Plot of Economic Health and PT Candidate's Vote Share

0.2

.4.6

.81

Eco

nom

y 20

10

.48 .49 .5 .51 .52Percent of the Vote Won by the PT Candidate

Elections Decided by a Three Percent Margin or LessEconomic Health

Graph 2: RDD of Economic Health and PT Candidate's Vote Share

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0.2

.4.6

.81

Eco

nom

y 20

10


Elections Decided by a Three Percent Margion or LessEconomic Health

Graph 3: Scatter Plot of Education and PT Candidate's Vote Share

.4.5

.6.7

.8.9

1E

duca

tion

2010


Elections Decided by a Three Percent Margin or LessEducation

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Graph 4: RDD of Education and PT Candidate's Vote Share.4

.5.6

.7.8

.91

Edu

catio

n 20

10


Elections Decided by a Three Percent Margin or LessEducation

Graph 5: Scatter Plot of Health Care and PT Candidate's Vote Share

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.5.6

.7.8

.91

Hea

lth C

are2

010


Elections Decided by a Three Percent Margin or LessHealth Care

Graph 6: RDD of Health Care and PT Candidate's Vote Share

.5.6

.7.8

.91

Hea

lth C

are

2010


Elections Decided by a Three Percent Margin or LessHealth Care

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Graph 7: Scatter Plot of Economic Health and Leftist Candidate's Vote Share

0.2

.4.6

.81

Eco

nom

y 20

10

.48 .49 .5 .51 .52Percent of the Vote Won by the Leftist Candidate

Elections Decided by a Three Percent Margin or LessEconomic Health: Left vs. Center

Graph 8: RDD of Economic Health and Leftist Candidate's Vote Share

Janusz 27

0.2

.4.6

.81

Eco

nom

y 20

10


Elections Decided by a Three Percent Margion or LessEconomic Health: Left vs. Center

Graph 9: Scatter Plot of Education and Leftist Candidate's Vote Share

.4.5

.6.7

.8.9

1E

duca

tion

2010

.48 .49 .5 .51 .52Percent of the Vote Won by Leftist Candidate

Elections Decided by a Three Percent Margin or LessEducation: Left vs. Center

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Graph 10: RDD of Education and Leftist Candidate's Vote Share

.4.5

.6.7

.8.9

1E

duca

tion

2010


Elections Decided by a Three Percent Margin or LessEducation: Left vs. Center

Graph 11: Scatter Plot of Economic Health and the Leftist Candidate's Vote Share

.5.6

.7.8

.91

Hea

lth C

are2

010


Elections Decided by a Three Percent Margin or LessHealth Care: Left vs. Center

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Graph 12: RDD of Health Care and Leftist Candidate's Vote Share.5

.6.7

.8.9

1H

ealth

Car

e 20

10


Elections Decided by a Three Percent Margin or LessHealth Care: Left vs. Center

Graph 13: Scatter Plot of Economic Health and the Leftist Candidate's Vote Share

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0.2

.4.6

.81

Eco

nom

y 20

10


Elections Decided by a Three Percent Margin or LessEconomic Health: Left vs. Right

Graph 14: RDD of Economic Health and Leftist Candidate's Vote Share

0.2

.4.6

.81

Eco

nom

y 20

10


Elections Decided by a Three Percent Margion or LessEconomic Health: Left vs. Right

Janusz 31

Graph 15: Scatter Plot of Education and the Leftist Candidate's Vote Share

.4.5

.6.7

.8.9

1E

duca

tion

2010


Elections Decided by a Three Percent Margin or LessEducation: Left vs. Right

Graph 16: RDD of Education and Leftist Candidate's Vote Share

Janusz 32

.4.5

.6.7

.8.9

1E

duca

tion

2010


Elections Decided by a Three Percent Margin or LessEducation: Left vs. Right

Graph 17: Scatter Plot of Health Score and the Leftist Candidate's Vote Share

.5.6

.7.8

.91

Hea

lth C

are2

010


Elections Decided by a Three Percent Margin or LessHealth Care: Left vs. Right

Janusz 33

Graph 18: RDD of Health Care and Leftist Candidate's Vote Share

.5.6

.7.8

.91

Hea

lth C

are

2010


Elections Decided by a Three Percent Margin or LessHealth Care: Left vs. Right

Graph 19: Scatter Plot of Economic Health and the Centrist Candidate's Vote Share

0.2

.4.6

.81

Eco

nom

y 20

10

.48 .49 .5 .51 .52Percent of the Vote Won by the Centrist Candidate

Elections Decided by a Three Percent Margin or LessEconomic Health: Center vs. Right

Janusz 34

Graph 20: RDD of Economic Health and Centrist Candidate's Vote Share0

.2.4

.6.8

1E

cono

my

2010


Elections Decided by a Three Percent Margion or LessEconomic Health: Center vs. Right

Graph 21: Scatter Plot of Education and the Centrist Candidate's Vote Share

Janusz 35

.4.5

.6.7

.8.9

1E

duca

tion

2010

.48 .49 .5 .51 .52Percent of the Vote Won by Centrist Candidate

Elections Decided by a Three Percent Margin or LessEducation: Center vs. Right

Graph 22: RDD of Education and Centrist Candidate's Vote Share

.4.5

.6.7

.8.9

1E

duca

tion

2010


Elections Decided by a Three Percent Margin or LessEducation: Center vs. Right

Janusz 36

Graph 23: Scatter Plot of Health Care and the Centrist Candidate's Vote Share

.5.6

.7.8

.91

Hea

lth C

are2

010

.48 .49 .5 .51 .52Percent of the Vote Won by Centrist Candidate

Elections Decided by a Three Percent Margin or LessHealth Care: Center vs. Right

Graph 24: RDD of Health Care and Centrist Candidate's Vote Share

Janusz 37

.5.6

.7.8

.91

Hea

lth C

are

2010


Elections Decided by a Three Percent Margin or LessHealth Care: Center vs. Right

Table 5: Full Sample Party StatisticsParty # Times Runner-up # Times ElectedDEM 437 473PC do B 70 39PCB 7 0PCO 1 0PDT 364 329PHS 26 13PMDB 898 1,127PMN 47 40PP 415 525PPS 221 129PR 305 372PRB 85 51PRP 33 16PRTB 33 11PSB 305 296PSC 87 58PSDB 597 758PSDC 41 8PSL 34 14

Janusz 38

PSOL 81 0PSTU 5 0PT 607 530PT do B 27 8PTB 347 382PTC 33 12PTN 36 15PV 139 75Total 5,281 5,281

Table 6: 3% Sample Party StatisticsParty # Times Runner-up # Times ElectedDEM 70 59PC do B 8 8PCO 1 0PDT 49 45PHS 5 0PMDB 110 158PMN 5 5PP 65 72PPS 25 13PR 41 42PRB 12 7PRP 5 3PRTB 2 2PSB 53 35PSC 13 7PSDB 74 116PSDC 6 3PSL 3 4PSOL 6 0PT 86 75

Janusz 39

PT do B 4 0PTB 53 51PTC 4 2PTN 4 1PV 12 8Total 716 716

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http://onlinelibrary.wiley.com/doi/10.1111/j.1548-2456.2004.tb00276.x/abstract

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