Effects of prohibition of coalitions in proportional elections on party and candidate behavior

Schaefer, Bruno Marques; Krause, Silvana; Mancuso, Wagner Pralon

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Revista de Sociologia e Política

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Artigo Original • Rev. Sociol. Polit. 32 • 2024 • https://doi.org/10.1590/1678-98732432e002 copy

Effects of prohibition of coalitions in proportional elections on party and candidate behavior

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT

Introduction:

Research indicates that the prohibition of party coalitions in proportional elections reduced party fragmentation in Brazilian Municipal Legislatures in 2020. However, existing studies have focused solely on the effect of the new legal rule on the party system at the local level. This article presents an alternative analysis to explore: 1) the influence of parties' electoral results in 2016 on their decisions to field candidates in 2020; 2) the impact of the electoral performance in 2016 on candidate party-switching in 2020; and 3) whether varying strategies employed by political elites (encompassing both party leaders and candidates) have influenced the level of party fragmentation.

Materials and methods:

We utilized data on party and individual performance in municipal proportional elections from 2016 to 2020, examining three units of analysis: municipality, party, and candidate. Various statistical methods, including binary logistic regression, multinomial regression, and linear regression, were employed to assess the impact of the prohibition of proportional coalitions on the behavior of political actors.

Results:

Our research reveals that higher party performance in 2016 increased the likelihood of fielding candidates in 2020 and reduced the probability of candidate defection from their initial party. Moreover, the interplay between strategies adopted by parties and candidates significantly influenced party fragmentation, as measured by the Effective Number of Parties.

Discussion:

The findings presented in our study significantly enhance our understanding of the implications of discontinuing proportional coalitions in Brazil. In addition to revealing a reduction in party fragmentation, our research underscores that this effect is mediated by the behavior of political elites, whether in the decision to field candidates (at the party level) or in the decision to migrate or remain in the same party (at the candidate level).

Keywords
party coalitions; proportional elections; party fragmentation; Effective Number of Parties; logistic regression

	2012	2016	2020
Total partidos	29	35	33
Total municípios	5.568	5.568	5.568
Número de listas possíveis	161.472	194.880	183.744
Número de listas reais	57.061	76.151	40.318
Proporção	0,35	0,39	0,22
Candidatos	413.051	437.380	495.355
Média de candidatos por lista	7,24	5,74	12,29

Partido (sigla)	Listas em 2016	Listas em 2020	Crescimento
PMB	905	161	-82,21
PMN	1221	317	-74,04
DC	1181	314	-73,41
PTC	1427	422	-70,43
PV	2542	863	-66,05
PcdoB	2229	791	-64,51
PCB	49	21	-57,14
CIDADANIA	2824	1225	-56,62
PSC	2731	1212	-55,62
SOLIDARIEDADE	2468	1171	-52,55
PRTB	1123	538	-52,09
REDE	703	343	-51,21
PSB	3971	1984	-50,04
PTB	3512	1757	-49,97
PSDB	4578	2444	-46,61
PDT	3855	2098	-45,58
PATRIOTA	1691	972	-42,52
PR	3575	2066	-42,21
REPUBLICANOS	2998	1954	-34,82
PSTU	73	48	-34,25
DEM	3599	2368	-34,20
MDB	5042	3338	-33,80
PSD	4200	2846	-32,24
PP	4164	2852	-31,51
PT	4169	2891	-30,65
PROS	2068	1563	-24,42
AVANTE	1284	989	-22,98
PODEMOS	1703	1420	-16,62
PSL	1848	1573	-14,88
PSOL	566	535	-5,48
PCO	13	15	15,38
NOVO	5	46	820,00

Variáveis	Estatísticas	Modelo 1 - básico	Modelo 2 - completo	Modelo 3 - básico (amostra)	Modelo 4 - completo (amostra)
Constante	Coeficiente	-0.029^* Signif. codes: * = 0.001;	-0.812^* Signif. codes: * = 0.001;	0.199^* Signif. codes: * = 0.001;	-0.858^* Signif. codes: * = 0.001;
	Erro padrão	0.008	0.075	0.027	0.141
	Exp(B)	0.970	0.443	1.221	0.423
Distância quociente (%)	Coeficiente	0.084^* Signif. codes: * = 0.001;	0.075^* Signif. codes: * = 0.001;	0.141^ = 0.01;	0.151^ = 0.01;
	Erro padrão	0.001	0.001	0.047	0.051
	Exp(B)	1.084	1.078	1.151	1.164
Ideologia	Coeficiente		-0.034		-0.184^* * = 0.05.
	Erro padrão		0.020		0.078
	Exp(B)		0.965		0.831
Magnitude do distrito	Coeficiente		0.135^* Signif. codes: * = 0.001;		0.158^* Signif. codes: * = 0.001;
	Erro padrão		0.002		0.008
	Exp(B)		1.114		1.171
IFDM (log)	Coeficiente		1.449^* Signif. codes: * = 0.001;		1.605^* Signif. codes: * = 0.001;
	Erro padrão		0.053		0.194
	Exp(B)		4.259		4.979
Cláusula de desempenho	Coeficiente		-1.112^* Signif. codes: * = 0.001;		-1.359^* Signif. codes: * = 0.001;
	Erro padrão		0.027		0.114
	Exp(B)		0.328		0.256
N		72.309	69.832	5.400	5.223
AIC		93.311	84.880	7.434,1	6.596,9

SG_PARTIDO	Mesmo partido	Partido maior	Partido menor
NOVO	81,25	0	18,75
PSTU	68	8	24
PT	61,96	13,71	24,33
PCO	50	0	50
PMDB	48,15	26,51	25,34
PSOL	46,57	16,87	36,57
PP	45,41	24,59	30
DEM	41,43	24,48	34,1
PSDB	40,81	28,69	30,5
PDT	37,62	26,95	35,43
PSD	36,84	29,34	33,82
PTB	32,74	31,17	36,09
REPUBLICANOS	31,99	27,44	40,58
PCdoB	30,41	24,17	45,42
PR	29,49	30,36	40,15
PSB	28,32	33,59	38,09
CIDADANIA	25,09	32,53	42,38
PV	23	33,94	43,06
PSC	22,67	32,47	44,85
SOLIDARIEDADE	20,31	32,94	46,76
AVANTE	19,49	29,94	50,57
REDE	18,48	25,69	55,83
PODEMOS	17,08	34,64	48,29
PCB	16,67	40	43,33
PATRIOTA	14,44	32,3	53,27
PSL	14,26	34,85	50,88
PMN	13,67	32,22	54,11
PROS	12,65	30,15	57,19
PRTB	9,92	34,14	55,93
PTC	9,69	37,01	53,3
DC	9,49	34,83	55,68
PMB	4,45	28,29	67,26

Variáveis	Estatísticas	Modelo 5		Modelo 6
		Partido maior (básico)	Partido menor (básico)	Partido maior (completo)	Partido menor (completo)
Constante	Coeficiente	0.086^* Signif. codes: * = 0.001;	0.261^* Signif. codes: * = 0.001;	-0.745^* Signif. codes: * = 0.001;	-0.402^* Signif. codes: * = 0.001;
	Erro padrão	0.008	0.007	0.031	0.034
	Exp(B)	1.089	1.298	0.474	0.6668
Distância quociente (%)	Coeficiente	-0.025^* Signif. codes: * = 0.001;	-0.099^* Signif. codes: * = 0.001;	-0.022^* Signif. codes: * = 0.001;	-0.098^* Signif. codes: * = 0.001;
	Erro padrão	0.000	0.001	0.000	0.001
	Exp(B)	0.974	0.905	0.978	0.906
Eleito em 2016	Coeficiente			-0.318^* Signif. codes: * = 0.001;	-0.318^* Signif. codes: * = 0.001;
	Erro padrão			0.017	0.017
	Exp(B)			0.727	0.845
Ideologia	Coeficiente			0.409^* Signif. codes: * = 0.001;	0.413^* Signif. codes: * = 0.001;
	Erro padrão			0.019	0.020
	Exp(B)			1.506	1.512
Magnitude do distrito	Coeficiente			0.014^* Signif. codes: * = 0.001;	-0.023^* Signif. codes: * = 0.001;
	Erro padrão			0.001	0.001
	Exp(B)			1.015	0.976
IFDM (log)	Coeficiente			-1.564^* Signif. codes: * = 0.001;	-2.229^* Signif. codes: * = 0.001;
	Erro padrão			0.058	0.060
	Exp(B)			0.209	0.100
Cláusula de desempenho	Coeficiente			0.875^* Signif. codes: * = 0.001;	0.930^* Signif. codes: * = 0.001;
	Erro padrão			0.029	0.029
	Exp(B)			2.400	2.535
N		116.773		114.125
AIC		243687.5		233161.1

Variáveis	Estatísticas	Modelo 7	Modelo 8
Constante	Coeficiente	-2,71^* Signif. codes: * = 0.001;	-6,69^* Signif. codes: * = 0.001;
	Erro padrão	0,16	0,12
Partidos grandes que se reapresentaram (%)	Coeficiente	0,029^* Signif. codes: * = 0.001;	0,030^* Signif. codes: * = 0.001;
	Erro padrão	0,001	0,001
Migração partidos maiores (%)	Coeficiente	0,010^* Signif. codes: * = 0.001;	0,010^* Signif. codes: * = 0.001;
	Erro padrão	0,001	0,001
Partidos grandes que se reapresentaram (%) × Migração partidos maiores (%)	Coeficiente	-0,002^* Signif. codes: * = 0.001;	-0,002^* Signif. codes: * = 0.001;
	Erro padrão	0,000	0,000
Diferença IFDM	Coeficiente		2,56^* Signif. codes: * = 0.001;
	Erro padrão		0,23
Diferença magnitude	Coeficiente		0,160*
	Erro padrão		0,070
N		4913	4676
Rs² Ajustado		0,04	0,07

Variável	N	Média	Desvio padrão	Mínimo	Máximo
Lançou candidato	72310
Não	40081	55.4%
Sim	32229	44.6%
Distância quociente (%)	72310	9.54	1.985	1.818	11.111
Ideologia	72310	0.205	0.401	-0.84	0.76
Magnitude	72310	11.239	3.826	7	55
IFDM	69833	0.669	0.1	0.321	0.901

Variável	N	Média	Desvio padrão	Mínimo	Máximo
Tipo migração	131156
… Mesmo partido	43910	33.5%
… Partido maior	37597	28.7%
… Partido menor	49649	37.9%
Distância quociente (%)	116773	3.841	9.975	-11.099	80.459
Eleito 2016	131156	0.306	0.461	0	1
Ideologia	116807	0.229	0.381	-0.84	0.76
Magnitude	116807	12.647	5.768	7	55
IFDM	114125	0.702	0.092	0.353	0.901

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[1] Bruno Marques Schaefer (brunoschaefer@iesp.uerj.br) é professor de Ciência Política no Instituto de Estudos Sociais e Políticos da Universidade do Estado do Rio de Janeiro.