Electoral Success and Political Institutionalization in the Federal Deputy Elections in Brazil (1998, 2002 and 2006)

Perissinotto, Renato; Bolognesi, Bruno

doi:10.1590/1981-3865201000010001

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Brazilian Political Science Review

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Article • Bras. Political Sci. Rev. 4 (1) • 2010 • https://doi.org/10.1590/1981-3865201000010001 copy

Electoral Success and Political Institutionalization in the Federal Deputy Elections in Brazil (1998, 2002 and 2006)¹ 1 The authors would like to thank Angel Miríade (UFSCar) and Camila Tribess (UFPR) for their preparation and correction work on the databases used in this article. They also thank the anonymous partners of the Brazilian Political Science Review, whose comments on the whole improved this text. Following convention, the remaining errors are the total responsibility of the authors.

Authorship SCIMAGO INSTITUTIONS RANKINGS

This article aims to identify the variables with the greatest impact on the chances of electoral success for candidates for the Brazilian Chamber of Deputies^* * Translator's note: the Brazilian Chamber of Deputies is the equivalent of the House of Representatives in the U.S. and the House of Commons in the U.K.; a Federal Deputy is the equivalent of a Congressman/Congresswoman in the U.S. and Member of Parliament in the U.K. in the 1998, 2002 and 2006 elections. Based upon data provided by the Supreme Electoral Court, this article firstly analyzes the relations between occupation, gender and level of education, on the one hand, and the electoral results (those elected and not elected), on the other. The article then presents a model of logistic regression in order to measure the real impact of these variables on the candidates’ chances of electoral success. The same procedure was repeated for the right-, center and left-wing parties. We conclude that being a professional politician is the most important variable in determining the electoral success of a Federal Deputy candidate in Brazil, in the elections that were analyzed.

Keywords:
Electoral success; Political institutionalization; Political recruitment; Elections; Political parties

	1998		2002		2006
Occupation^* * The association between the candidate's occupation and the condition of elected proved to be significant in all years (p=0.000). The contingency coefficient was 0.32; 0.36 and 0.45 for 1998, 2002 and 2006, respectively.	Non-elected (%)^ N = 11.116	Elected (%)^* ***** N = 1539	Non-elected (%)^ N = 11.116	Elected (%)^* ***** N = 1539	Non-elected (%)^ N = 11.116	Elected (%)^* ***** N = 1539
Economist	1.7	3.5	0.9	1.9	1.0	1.6
Engineer	3.4	7.2	2.2	5.7	1.9	4.7
Doctor	4.9	9.9	4.0	8.4	3.9	8.0
Lawyer	11.4	15.4	11.0	14.6	10.2	8.8
Politician of Legislative Power^** ****** The Supreme Electoral Court's information registers political activity in a different way for each election. In 1998, Senators, Deputies and Councilors were registered as “members of the Legislative Power” (N=233); in 2002, in a single category “Senators, Deputies, Councilors” (N=298) and in 2006 Senators (N=1), Deputies (N=348) and Councilors (N=181) were registered separately. In order for us to compare the relationship between occupation and electoral success for the three elections we grouped together all of these categories in one: “Politicians of Legislative Power”.	4.2	21.4	3.9	29.0	6.6	46.8
Trader	5.7	1.8	6.2	1.2	6.4	1.6
State servant	4.5	1.4	3.2	1.0	3.3	0.8
Federal servant	2.2	0.2	3.0	0.6	3.2	1.2
Businessperson	-	-	7.0	4.5	7.8	6.2
Industrialist	1.1	1.4	0.3	0.6	0.2	0.2

	1998		2002		2006
Variables	Non-elected (%)	Elected (%)	Non-elected (%)	Elected (%)	Non-elected (%)	Elected (%)
Gender
Male	88.8	94.3	88.2	91.8	86.9	91.2
Female	11.2	5.7	11.8	8.2	13.1	8.8
Education
Reads and writes	0.6	0.2	1.2	0.4	0.2	0.2
Primary education incomplete	3.9	1.0	5.2	1.6	3.7	1.0
Completed primary education	4.2	0.6	6.6	2.1	7.6	1.4
Secondary education incomplete	5.0	1.9	6.1	1.2	3.6	0.6
Completed secondary education	17.3	9.6	19.4	9.7	23.5	9.0
Higher education incomplete	12.2	6.8	11.6	9.2	11.7	7.4
Completed higher education	55.5	79.1	47.9	74.9	49.6	80.5
Not given	1.3	0.8	2.0	1.0	0.0	0.0

	1998	2002	2006
Political variables
Professional politician	6.628^ p<0.01	12.074^ p<0.01	13.318^ p<0.01
PCdoB	3.235^* * p<0.05	6.048^ p<0.01	4.423^ p<0.01
PDT	1.227	1.335	1.384
PFL	7.855^ p<0.01	9.151^ p<0.01	5.655^ p<0.01
PMDB	3.833^ p<0.01	4.599^ p<0.01	5.010^ p<0.01
PPS	0.351	1.325	1.504
PSB	1.632	1.227	1.627
PSDB	6.090^ p<0.01	4.626^ p<0.01	3.988^ p<0.01
PT	3.150^ p<0.01	5.418^ p<0.01	4.738^ p<0.01
PTB	2.777^* * p<0.05	2.171^* * p<0.05	1.465
PL	2.458^ p<0.01	1.698^* * p<0.05	1.883^* * p<0.05
PSOL ¹	-	-	0.453
Demographic variables
Being a man	1.986^* * p<0.05	1.535^* * p<0.05	1.301
Having a degree	1.953^* * p<0.05	1.993^ p<0.01	2.842^ p<0.01
Above 40 years of age	1.143	1.752^ p<0.01	1.323
Societal variables
Lawyer	1.502^* * p<0.05	1.909^ p<0.01	1.410
Economist	1.992^* * p<0.05	2.432^* * p<0.05	2.674^* * p<0.05
Engineer	1.949^* * p<0.05	2.885^ p<0.01	3.936^ p<0.01
Doctor	2.019^ p<0.01	2.581^ p<0.01	3.568^ p<0.01
Industrialist	1.596	5.331^* * p<0.05	4.948
Priest	3.112^* * p<0.05	6.688^ p<0.01	1.827
Businessperson	-	1.279	2.460^ p<0.01
Cattle farmer	-	2.785	9.737^ p<0.01

Occupation	Right		Center		Left
1998	Non-elected	Elected	Non-elected	Elected	Non-elected	Elected
Lawyers	11.8	16.0	14.3	14.3	10.5	15.9
Bank clerk	0.6	0.0	0.7	1.1	2.6	4.4
Trader	6.1	2.8	5.0	0.5	4.4	1.8
Economist	2.2	3.3	2.4	3.8	0.9	3.5
Engineer	2.4	9.0	6.7	6.0	3.6	5.3
Industrialist	1.9	1.4	1.3	1.6	0.4	0.9
Doctor	5.6	7.5	7.4	11.5	4.4	12.4
Metallurgist	0.1	0.0	0.2	0.0	0.8	1.8
Legislative politician	2.8	18.9	6.3	26.4	5.4	19.5
State servant	4.8	1.4	4.1	2.2	3.6	0.0
Federal servant	1.5	0.5	2.6	0.0	2.7	0.0
2002	Non-elected	Elected	Non-elected	Elected	Non-elected	Elected
Lawyers	10.8	13.0	15.1	15.8	10.7	14.5
Bank clerk	0.2	0.0	0.9	0.7	1.8	2.4
Trader	6.8	0.0	4.0	1.4	5.2	1.8
Economist	0.8	2.1	2.4	2.7	0.7	1.2
Businessperson	8.3	5.7	12.6	6.8	4.5	1.2
Engineer	2.0	6.2	3.1	6.2	2.5	4.8
Industrialist	0.3	1.0	0.4	0.7	0.2	0.0
Doctor	3.4	5.2	7.1	10.3	4.5	10.8
Metallurgist	0.0	0.5	0.0	0.0	0.3	0.0
Cattle farmer	0.3	2.1	1.8	0.0	0.3	0.0
Legislative politician	3.5	33.2	6.4	30.8	4.5	23.5
Priest	1.2	3.6	0.2	0.7	0.8	1.2
State servant	3.5	0.0	2.2	2.7	2.9	0.6
Federal servant	2.8	0.5	2.0	0.0	4.2	1.2
2006	Non-elected	Elected	Non-elected	Elected	Non-elected	Elected
Lawyers	9.7	6.7	12.1	9.0	11.4	10.3
Bank clerk	0.3	0.6	0.2	0.0	1.4	1.6
Trader	8.1	1.8	4.0	1.3	4.6	1.1
Economist	1.2	1.8	0.8	1.3	0.8	1.6
Businessperson	8.5	7.3	11.1	7.1	6.4	3.8
Engineer	2.0	7.3	2.2	6.5	1.9	1.1
Industrialist	0.1	0.6	0.2	0.0	0.2	0.0
Doctor	3.5	6.7	4.3	5.2	4.3	11.9
Metallurgist	0.1	0.0	0.0	0.0	0.1	1.6
Cattle farmer	0.3	1.8	0.8	0.0	0.2	1.1
Legislative politician	7.5	46.7	10.6	43.0	6.6	43.3
Priest	1.7	0.6	1.0	0.6	0.2	0.0
State servant	3.0	0.6	2.8	1.3	3.5	0.5
Federal servant	2.1	0.0	2.2	1.3	4.5	1.6

Variables	Right		Center		Left
	Non-elected (%)	Elected (%)	Non-elected (%)	Elected (%)	Non-elected (%)	Elected (%)
1998
Gender
Male	89.7	97.6	88.0	91.8	88.0	92.0
Female	10.3	2.4	12.0	8.2	12.0	8.0
Education
Reads and writes	0.5	0.5	0.0	0.0	0.6	0.0
Primary education incomplete	3.9	0.9	3.3	0.0	3.3	2.7
Completed primary education	5.2	0.5	2.2	0.5	3.7	0.9
Secondary education incomplete	5.9	2.4	2.0	1.6	5.0	0.9
Completed secondary education	18.1	12.3	14.1	9.3	15.6	5.3
Higher education incomplete	12.2	5.2	9.6	6.6	13.3	9.7
Completed higher education	52.6	77.4	68.0	81.3	57.8	80.5
Not given	1.6	0.9	0.9	0.5	0.8	0.0
2002
Gender
Male	88.8	95.3	87.1	93.2	87.2	87.3
Female	11.1	4.7	12.9	6.8	12.8	12.7
Education
Reads and writes	1.5	0.0	1.6	0.7	0.8	0.6
Primary education incomplete	5.5	2.1	2.7	0.0	4.3	2.4
Completed primary education	7.9	2.6	3.3	2.1	5.0	1.8
Secondary education incomplete	5.4	1.0	5.3	2.1	5.8	0.0
Completed secondary education	22.2	10.9	16.2	8.9	16.4	7.8
Higher education incomplete	11.2	7.3	10.9	8.2	13.0	12.7
Completed higher education	44.7	75.1	59.2	78.1	52.9	72.9
Not given	1.7	1.0	0.9	0.0	1.8	1.8
2006
Gender
Male	88.8	93.9	85.2	92.3	86.3	88.1
Female	11.2	6.1	14.8	7.7	13.7	11.9
Education
Reads and writes	0.1	0.0	0.0	0.0	0.2	0.5
Primary education incomplete	3.1	1.2	1.0	0.6	4.0	1.1
Completed primary education	9.2	1.8	5.7	1.3	5.7	1.1
Secondary education incomplete	3.9	1.2	3.0	0.6	3.0	0.0
Completed secondary education	23.6	11.6	16.6	5.2	20.9	9.2
Higher education incomplete	3.9	1.2	12.2	7.1	11.6	9.2
Completed higher education	45.1	78.7	61.5	85.2	54.6	78.9
Not given	---	---	---	---	0.1	---

Predictive variables	Right	Center	Left
1998
Political variables
Professional politician	9.462^ p<0.01	6.590^ p<0.01	6.410^ p<0.01
Demographic variables
Being a man	3.812^* * p<0.05	1.339^* * p<0.05	1.482
Having a degree	2.373^ p<0.01	1.838^* * p<0.05	2.363^* * p<0.05
Above 40 years of age	1.125	0.930	1.346
Societal variables
Lawyer	1.442	1.333	1.917^* * p<0.05
Economist	1.754	2.139	4.880^* * p<0.05
Engineer	3.785^ p<0.01	1.180	1.858
Doctor	1.389	2.092^* * p<0.05	3.519^* * p<0.05
Priest	3.157	0.000	0.000
Industrialist	1.157	2.442	4.174
Metallurgist	0.000	0.000	5.976^* * p<0.05
2002
Political variables
Professional politician	21.111^ p<0.01	7.863^ p<0.01	8.727^ p<0.01
Demographic variables
Being a man	2.079	1.589	1.108
Having a degree	3.624^ p<0.01	1.851^* * p<0.05	1.877^* * p<0.05
Above 40 years of age	1.417	1.440^* * p<0.05	1.920^* * p<0.05
Societal variables
Lawyer	1.552	1.422	1.618
Economist	3.090	1.616	1.976
Engineer	3.656^* * p<0.05	2.505	2.093
Doctor	1.796	1.870	2.705^* * p<0.05
Priest	9.756^ p<0.01	5.301	2.548
Industrialist	9.069^* * p<0.05	3.864	0.000
Metallurgist	0.000	---	0.000
Businessperson	1.915	1.118	0.510
Cattle farmer	16.906^ p<0.01	0.000	0.000
Bank clerk	0.000	1.371	1.867
2006
Political variables
Professional politician	16.970^ p<0.01	12.335^ p<0.01	16.320^ p<0.01
Demographic variables
Being a man	1.137	1.574	1.074
Having a degree	3.569^ p<0.01	2.968^ p<0.01	2.670^ p<0.01
Above 40 years of age	0.923	1.841	1.582
Societal variables
Lawyer	1.243	1.480	1.612
Economist	3.063	2.764	3.475
Engineer	6.621^ p<0.01	5.026^* * p<0.05	1.021
Doctor	3.385^* * p<0.05	2.360	4.654^ p<0.01
Priest	1.601	2.197	0.000
Industrialist 2	58.954^* * p<0.05	0.000	0.000
Metallurgist	0.000	0.000	71.225^ p<0.01
Businessperson	3.078^* * p<0.05	2.103	1.791
Cattle farmer	24.768^ p<0.01	0.000	12.871^* * p<0.05
Bank clerk	6.127	0.000	2.784

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[1] 1
The authors would like to thank Angel Miríade (UFSCar) and Camila Tribess (UFPR) for their preparation and correction work on the databases used in this article. They also thank the anonymous partners of the Brazilian Political Science Review, whose comments on the whole improved this text. Following convention, the remaining errors are the total responsibility of the authors.