Using Voter-choice Modeling to Plan Final Campaigns in Runoff Elections

Even though runoff elections are the most common form of presidential elections in the world, voter-choice behavior in these two-round elections have not received the attention they deserve in the literature. Two-round elections provide political consultants and candidates with rich and factual data on voter preferences, revealed through the voting behavior observed in the first round, which can guide the planning and implementation of their final campaign. They also allow political analysts to apply their voter-choice models to actual voting behavior (rather than voting intentions) in a multi-party election during the first round, and validate their predictions in a two-party election in the final round. I use results from the four most recent Brazilian presidential elections to demonstrate how voter-choice models can be applied to guide political campaigns in runoff elections.

Key words:
political marketing; runoff elections; multi-party elections; nested-logit; unobserved heterogeneity

Authorship

Wagner Antonio Kamakura

Rice UniversityRice UniversityUSAUSARice University

Wagner Antonio Kamakura 6100 Main Street MS531, 77005-1892, Houston, Texas, United States. E-mail: kamakura@rice.edu

SCIMAGO INSTITUTIONS RANKINGS

Rice UniversityRice UniversityUSAUSARice University

Figures | Tables | Formulas

Figures (4)
Tables (6)
Formulas (5)

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Figure 1
Geographic Distribution of Votes and the Human Development Index

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Figure 2
Latent Space of Candidates and Districts Estimated by the Voter-choice Model

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Figure 3
Number of Votes for the Third-place Candidate (Marina-PSB) Accumulated within 50Km from each Location

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Figure 4
Voter-Potential Accumulated within 50Km from each Location

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Table 1
Voter Intentions Gathered Via Opinion Polls Before the First and Second Rounds of the 2014 Presidential Elections in Brazil

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Table 2
Estimated Markov Transition Matrix for the Brazilian Presidential Elections

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Table 3
Parameter Estimates of the Voter-choice Model for the First Round of the 2014 Presidential Election in Brazil

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Table 4
Markov Transition Matrix Implied by the Voter-choice Model Estimated from the First Round of 2014

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Table 5
Expected Percentage of Final Valid Votes for Aécio Neves under Multiple Scenarios of Vote-Transfer from Marina Silva

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Table 6
Estimated Markov Transition Matrix from the 2014 Presidential Elections in Brazil

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Figure 1 Geographic Distribution of Votes and the Human Development Index

Source: Produced by the author based on data from Programa das Nações Unidas para o Desenvolvimento. (n.d.). Ranking IDHM Municípios 2010. Retrieved from http://www.pnud.org.br/atlas/ranking/Ranking-IDHM-Municipios-2010.aspx

Figure 2 Latent Space of Candidates and Districts Estimated by the Voter-choice Model

Figure 3 Number of Votes for the Third-place Candidate (Marina-PSB) Accumulated within 50Km from each Location

Figure 4 Voter-Potential Accumulated within 50Km from each Location

Table 1 Voter Intentions Gathered Via Opinion Polls Before the First and Second Rounds of the 2014 Presidential Elections in Brazil

	Date	Dilma (PT)	Aécio (PSDB)	Marina (PSB)	Abstentions*
First Round - Actual	5-Oct	30.3%	24.4%	15.5%	27.2%
Voter intention	4-Oct	40%	24%	22%	14%
	2-Oct	40%	21%	24%	15%
	26-Sep	40%	18%	27%	15%
	19-Sep	37%	17%	30%	16%
Second Round - Actual	26-Oct	38.2%	31.9%	-	30.0%
Voter intention	25-Oct	47%	42%	--	11%
	22-Oct	47%	43%	--	10%
	16-Oct	43%	45%	--	12%

Note. Source: Instituto de Pesquisa Datafolha. (2014, September 19). Brasil eleições 2014, intenções de votos para presidência da República (Relatório nº PO813761). Retrieved from http://media.folha.uol.com.br/datafolha/2014/09/19/intencao_de_voto_presidente.pdf; Instituto de Pesquisa Datafolha. (2014, September 26). Brasil eleições 2014, intenções de votos para presidência da República (Relatório nº PO813763). Retrieved from http://media.folha.uol.com.br/datafolha/2014/09/27/intencaodevotoeavaliacaopresidente.pdf; Instituto de Pesquisa Datafolha. (2014, October 4). Brasil eleições 2014, intenções de votos para presidência da República (Relatório nº PO813765). Retrieved from http://media.folha.uol.com.br/datafolha/2014/10/04/intencao_de_voto_presidente.pdf; Instituto de Pesquisa Datafolha. (2014, October 16). Brasil eleições 2014, intenções de votos para presidência da República- 2^o turno (Relatório nº PO813773). Retrieved from http://media.folha.uol.com.br/datafolha/2014/10/15/intencao-de-voto-presidente-2-turno.pdf; Instituto de Pesquisa Datafolha. (2014, October 22). Brasil eleições 2014, intenções de votos para presidência da República - 2^o turno (Relatório nº PO813775). Retrieved from http://media.folha.uol.com.br/datafolha/2014/10/22/intencao_de_voto_presidente_2_turno.pdf; Instituto de Pesquisa Datafolha. (2014 October 24). Brasil eleições 2014, intenções de votos para presidência da República - 2^o turno (Relatório nº PO813776). Retrieved from http://media.folha.uol.com.br/datafolha/2014/10/25/intencao_de_voto_presidente_vespera_2_turno.pdf
^*
Abstentions also include undecided voters in opinion polls

Table 2 Estimated Markov Transition Matrix for the Brazilian Presidential Elections

2002		From first round
2002		Abstention	Lula (PT)	José Serra (PSDB)	Garotinho	Ciro Gomes	Others	Votes (MM)
To second round	Abstention	84%	0%	0%	20%	16%	0%	29.1
	Lula (PT)	0%	100%	0%	58%	44%	100%	52.8
	José Serra (PSDB)	16%	0%	100%	22%	40%	0%	33.4
To second round	Abstention	97%	0%	2%	6%	43%	0%	30.0
	Lula (PT)	3%	100%	10%	74%	57%	100%	58.3
	Alckmin (PSDB)	0%	0%	88%	19%	1%	0%	37.5
	Votes (MM)	29.9	46.6	40.0	6.6	2.5	0.3	125.8
2010		From first round				2.5	0.3	125.8
2010		Abstention	Dilma (PT)	José Serra (PSDB)	Maria Silva	Plinio	Others	Votes (MM)
To second round	Abstention	99%	0%	0%	20%	100%	100%	36.3
	Dilma (PT)	0%	100%	0%	28%	0%	0%	55.8
	José Serra (PSDB)	1%	0%	100%	52%	0%	0%	43.7
	Votes (MM)	34.2	47.7	33.1	19.6	0.9	0.3	135.8

Table 3 Parameter Estimates of the Voter-choice Model for the First Round of the 2014 Presidential Election in Brazil

Candidate	Intercept	Factor 1	Factor 2	Factor 3	% under 25	% 60 or older	HDI_ Educ	HDI- Long	HDI- Income
Abstention	0.000	0.253	0.046	0.231	0.000	0.000	0.000	0.000	0.000
Dilma	1.103	-0.280	0.266	0.117	0.687	-0.100	0.187	-0.011	-0.398
Aécio	0.195	0.339	0.588	-0.308	1.824	0.076	0.287	0.263	-0.081
Marina	0.291	-0.098	-0.548	-0.045	-0.589	-0.210	0.382	-0.228	0.058
Luciana	-2.090	-0.089	-0.081	0.000	-4.718	-0.060	0.440	-0.008	0.308
Pastor	-3.530	-0.027	-0.062	0.063	3.047	-0.267	0.178	0.017	0.015
Eduardo	-3.602	0.060	0.025	-0.185	-1.634	0.035	0.505	0.074	0.233
Others (Right)	-3.826	-0.017	-0.165	0.036	0.541	-0.226	0.403	-0.026	0.149
Others (Left)	-4.797	-0.141	-0.067	0.092	-0.048	-0.063	0.550	-0.230	0.043
Within-district std. deviation	--	0.358	0.410	0.855	--	--	--	--	--
Coefficient of dissimilarity	0.451

Note. Values in bold are statistically significant at the 0.01 level.

Table 4 Markov Transition Matrix Implied by the Voter-choice Model Estimated from the First Round of 2014

		From first round
		Abstention	Dilma (PT)	Aécio (PSDB)	Marina	Luciana	Pastor	Eduardo	Others (right)	Others (left)	Votes (MM)
To second round	Abstention	99%	2%	1%	20%	0%	0%	0%	100%	0%	42.8
	Dilma (PT)	0%	98%	0%	67%	100%	100%	0%	0%	100%	54.5
	Aécio (PSDB)	1%	0%	99%	13%	0%	0%	100%	0%	0%	45.5

Table 5 Expected Percentage of Final Valid Votes for Aécio Neves under Multiple Scenarios of Vote-Transfer from Marina Silva

		% of valid votes for Aécio in the second round among Marina voters
		50%	55%	60%	65%	70%	75%
% of abstention in second round among Marina voters	0%	46.7%	47.8%	48.9%	50.0%	51.1%	52.3%
	5%	46.6%	47.7%	48.7%	49.8%	50.9%	51.9%
	10%	46.5%	47.6%	48.6%	49.6%	50.6%	51.6%
	15%	46.5%	47.5%	48.4%	49.4%	50.4%	51.3%

Table 6 Estimated Markov Transition Matrix from the 2014 Presidential Elections in Brazil

		From first round
		Abstention	Dilma	Aécio	Marina	Luciana	Pastor	Eduardo	Others (right)	Others (left)	Votes (MM)
To second round	Abstention	97%	2%	0%	2%	0%	0%	0%	0%	0%	37.3
	Dilma	0%	98%	0%	44%	9%	100%	0%	0%	100%	54.5
	Aécio	3%	0%	100%	54%	91%	0%	100%	100%	0%	51.0
	Votes (MM)	38.8	43.3	34.9	22.2	1.6	0.8	0.6	1.5	0.2	142.8

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Using Voter-choice Modeling to Plan Final Campaigns in Runoff Elections

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[1] Wagner Antonio Kamakura 6100 Main Street MS531, 77005-1892, Houston, Texas, United States. E-mail: kamakura@rice.edu