The Impact of New Technologies on Voter Confidence in Latin America: Evidence from E-Voting Experiments in Argentina and Colombia

Figures & data

TABLE 1. The Road to E-Voting (EV) in Latin America: Summary of Electronic Elections and E-Voting Pilot Tests throughout the Region

Country	Type of implementation:pilot (binding or not) or roll-out^a	Type of election (highest level)	Year of first EV election/pilot	% of registered e-voters (last election)	Type of EV technology
Argentina	Several binding and nonbinding pilots	Provincial	2003	N/A	Several devices (including Brazilian DRE)
Brazil	Roll-out for all type of elections	National	1996	100 (since 2000)	DRE (two terminals): one for voter registration and another for casting a ballot
Colombia	Nonbinding pilots	Local	1992	N/A	Several devices
Costa Rica	Binding pilot	Local	2002	2.3
Dominican Republic	Planned to roll out in 2006 elections. procurement did take place but was not implemented. Used in primary of the incumbent party	Primary of governing party	2006	–	Brazilian DRE
Ecuador	Binding pilot. It was planned to continue in 2006 but was cancelled	Local	2004	0.7 (2004)	Brazilian DRE
Mexico	Nonbinding pilot	Local	2006	N/A	Several devices
Panama	Election authorities announced roll out for the 2006 Canal referendum but cancelled the implementation	–	–	–	–
Paraguay	Roll out in the 2003 presidential election but went back to paper ballots in 2008	National	2001	53 (2003)	Brazilian DRE
Peru	Several nonbinding and binding pilots	Provincial	1996	N/A	Brazilian DRE
Venezuela	Roll-out for all types of elections	National	1998	100 (since 1998)	Optical scanner (1998–2000); DRE (2004 onwards)
^aRoll out – at least two consecutive binding elections. Otherwise, it is categorized as a pilot.

FIGURE 1. Prototypes tested in the Argentine e-voting pilot.

FIGURE 2. Prototypes tested in the Colombian e-voting pilot (color figure available online).

TABLE 2. Percentage of Positive Responses to the Survey Question “Are you confident that your vote was recorded as intended?”

Sociodemographic and technological variables	Argentina	Colombia
Age
18–29	94.1	91.8
30–50	92.3	94.6
>50	94.6	95.7
Education
Secondary or less	94.1	95.8
College	93.2	92.6
Gender
Female	93.8	94.8
Male	93.2	93.5
E-voting technology
DRE with VVAT	93.6	96.0
DRE without VVAT	95.0	94.0
OS	92.3	89.9
Whole sample	93.6	94.0
Sample size (N)	2,792	2,245

TABLE 3. Parameter Estimates and Standard Errors (in Parenthesis) for Models 1–3 Examining Confidence in E-Voting^a

Independent variables	Model 1–joint sample(probit)	Model 2–Argentina (bivariate probit)		Model 3–Colombia (bivariate probit)
	Confident vote was recorded as intended	Confident vote was recorded as intended	E-voting is easy	Confident vote was recorded as intended	E-voting is easier than traditional paper ballot
Age: 30–50	−0.14 (0.10)	−0.15 (0.10)	−0.07 (0.08)	0.23** (0.10)	0.25** (0.10)
Age: >50	0.04 (0.11)	0.07 (0.11)	−0.25*** (0.09)	0.33** (0.13)	0.15 (0.12)
College Education	−0.06 (0.08)	−0.10 (0.09)	0.01 (0.07)	−0.26*** (0.09)	−0.25*** (0.09)
Female	0.08 (0.06)	0.04 (0.08)	0.00 (0.06)	0.12 (0.09)	0.07 (0.09)
DRE	0.25*** (0.07)	0.21** (0.10)	0.20*** (0.07)	0.30*** (0.11)	−0.01 (0.12)
VVAT	0.01 (0.07)	−0.14 (0.10)	0.04 (0.07)	0.19* (0.11)	0.02 (0.11)
Colombia	−0.05 (0.14)
Age 30–50 * Colombia	0.37*** (0.14)
Age >50 * Colombia	0.28* (0.17)
College education * Colombia	−0.23* (0.12)
Voting problems		−0.45*** (0.11)	−0.33*** (0.09)
Political information		0.01 (0.03)	0.01 (0.02)
Use of technology		0.05 (0.06)	0.07* (0.04)
Bogotá				−0.12 (0.12)	0.22* (0.11)
Pereira				−0.07 (0.13)	0.22* (0.12)
Intercept	1.40*** (0.11)	1.56*** (0.13)	0.99*** (0.10)	1.29*** (0.14)	1.40*** (0.14)
Correlation between dependent variables		0.38*** (0.05)		0.36*** (0.07)
Pseudo-R squared	0.03	0.04		0.02
p-value: Hosmer–Lemeshow test^b	0.80	0.99		0.43
L-R test statistic	45.81***	79.10***		56.96***
Sample size (N)	5,037	2,792		2,245
^aStandard errors in parenthesis. Significance levels: ***0.01, **0.05, *0.1.
^bIn the case of Models 2 and 3, we use the adaptation of the Hosmer–Lemeshow test to the bivariate probit model proposed by Chiburis, Das, and Lokshin (2010). The null hypothesis is that there is no difference between observed and predicted values of the response variables.

FIGURE 3. Marginal effects of selected covariates on the perceived reliability and usability of electronic voting machines. Figure 3 plots the average effect of a change in selected covariates on the probability of a positive response to the confidence and usability questions, in percentage points. The central dots represent the point estimates (means), while the vertical lines correspond to the 95% confidence intervals.

TABLE 4. Percentage of Positive Responses to Survey Items Comparing Electronic and Manual Voting

Sociodemographic and technological variables	Argentina		Colombia
	Would like to use e-voting in real elections	E-voting should replace traditional system	E-voting is more reliable than traditional system	More confident that votes are counted
Age
18–29	95.3	68.8	79.4	82.8
30–50	96.8	78.6	86.6	89.3
>50	97.4	81.1	93.0	90.6
Education
Secondary or less	97.2	79.3	90.7	90.7
College	96.5	76.8	82.1	85.4
Gender
Female	97.1	76.4	86.2	87.6
Male	96.4	79.3	85.5	87.7
E-voting technology
DRE with VVAT	97.4	78.9	86.6	87.3
DRE without VVAT	96.7	77.4	85.8	87.0
OS	96.0	77.1	83.9	89.0
Whole sample	96.8	77.7	85.8	87.6
Sample size (N)	2,426		2,245

TABLE 5. Parameter Estimates and Standard Errors (in Parenthesis) for Models 4–5 Comparing E-Voting and Paper-Based Methods^a

Independent variables	Model 4–Argentina(bivariate probit)		Model 5—Colombia(bivariate probit)
	Would like to use e-voting in real elections	E-voting should replace traditional system	E-voting is more reliable than traditional system	More confident that votes are counted
Age: 30–50	0.22* (0.13)	0.36*** (0.08)	0.30*** (0.07)	0.30*** (0.08)
Age: >50	0.24* (0.14)	0.41*** (0.09)	0.64*** (0.11)	0.33*** (0.10)
College education	−0.05 (0.11)	−0.02 (0.07)	−0.41*** (0.07)	−0.29*** (0.07)
Female	0.10 (0.10)	−0.08 (0.10)	0.08 (0.07)	0.05 (0.07)
DRE	0.11 (0.12)	0.09 (0.08)	0.11 (0.09)	−0.10 (0.10)
VVAT	0.11 (0.13)	−0.06 (0.08)	−0.01 (0.07)	−0.02 (0.08)
Voting problems	−0.07 (0.17)	−0.07 (0.11)
Political information	0.00 (0.05)	0.02 (0.03)
Use of technology	−0.05 (0.08)	0.02 (0.05)
Bogotá			0.08 (0.09)	0.14 (0.09)
Pereira			0.11 (0.09)	0.25*** (0.10)
Intercept	1.56*** (0.16)	0.75*** (0.10)	0.89*** (0.11)	1.04*** (0.11)
Correlation between dependent variables	0.64*** (0.05)		0.70*** (0.03)
Pseudo-R squared	0.09		0.19
p-value: Hosmer–Lemeshow test^b	0.68		0.35
L-R test statistic	40.66***		92.89***
Sample size (N)	2,426		2,245
^aStandard errors in parenthesis. Significance levels: ***0.01, **0.05, *0.1.
^bWe use the adaptation of the Hosmer–Lemeshow test to the bivariate probit model proposed by Chiburis, Das, and Lokshin (2010). The null hypothesis is that there is no difference between observed and predicted values of the response variables.