1 Online Appendix for
“The Link Between Voting and Life Satisfaction in Latin America”
Rebecca Weitz-Shapiro ([email protected]) and Matthew S. Winters ([email protected])
(1) Description and Summary Statistics for Variables Used in Analysis
Variable English Spanish N Mean S.D. Min Max satisfaction
with life
In general, have you been satisfied with your life? Would you say that you are ..? (4) Very satisfied (3) Somewhat satisfied (2) Somewhat unsatisfied (1) Very unsatisfied
En general ¿hasta qué punto se encuentra satisfecho con su vida? ¿Diría usted que se encuentra ..? (4) Muy satisfecho (3) Algo satisfecho (2) Algo insatisfecho (1) Muy
insatisfecho
29,483 3.18 0.80 1 4
voted Did you vote in the last presidential election?
¿Votó usted en las últimas elecciones presidenciales?
29,200 0.76 0.43 0 1
male 29,738 0.48 0.50 0 1
education (standardized by country by subtracting the mean and dividing by two standard deviations)
What was the last year of education you passed?
¿Cuál fue el último año de enseñanza (educación, o escuela) que usted completó o aprobó?
29,738 0.00 0.50 -1.37 1.40
age 29,668 38.9 15.9 16 101
wealth The salary or wage that you receive and all of your family income:
(4) Covers every one well and allows you to save
(3) Covers everyone without big
difficulties
(2) Does not cover everyone; you have difficulties
(1) Does not cover everyone; you have big difficulties
El salario o sueldo que usted recibe y el total del ingreso familiar:
4. Les alcanza bien, pueden ahorrar 3. Les alcanza justo sin grandes
dificultades 2. No les alcanza, tienen dificultades 1. No les alcanza, tienen grandes dificultades
2 income In which of the
following categories is the family income of this household, including external remittances and the income of all adults and children who work? (11 categories based on local income scale)
¿En cuál de los siguientes rangos se encuentran los ingresos familiares mensuales de este hogar, incluyendo las remesas del exterior y el ingreso de todos los adultos e hijos que
trabajan?
26,193 4.10 2.26 0 10
married (1) married or cohabitating; (0) single, divorced, separated or widowed
(1) casado o unión libre (acompañado); (0) soltero,
divorciado, separado o viudo
29,456 0.59 0.49 0 1
children (recoded to be 0/1)
How many children do you have?
¿Tiene hijos(as)?
¿Cuántos? 29,650 0.73 0.44 0 1
minority (recoded to be 0/1)
Do you consider yourself white, mestizo, indigenous, of African origin, mulato or something else?
(0) white or mestizo; (1) indigenous, African, mulato or other1
¿Usted se considera una persona (1) blanca, (2)
mestiza,(3) indígena u originaria, (4) negra o Afro-, (5) mulata, u (6) otra?
28,775 0.17 0.37 0 1
Country-Level Variables GDP per
capita PPP
GDP per capita PPP in 2000 U.S. dollars (from World Development Indicators)
18 8,388 3,658 2,483 13,406
PolityIV Polity2 (from PolityIV dataset, 2009
version)
18 8 1.46 5 10
voting enforced
Enforced compulsory voting (author’s coding; see footnote in text)
18 0.5 0.51 0 1
1
3 (2) Ordered Logistic Regression Model with Country Fixed Effects
Using an ordered logistic regression model instead of a linear model produces results in which all variables match in direction and significance level with the linear model reported in the text. Most importantly, voting is a significant, positive predictor of life satisfaction.
b/se voted 0.168*** (0.032) male -0.023 (0.025) Education 0.118*** (0.031) age -0.027*** (0.005) age*age 0.000*** (0.000) wealth 0.435*** (0.018) income 0.048*** (0.007) married 0.239*** (0.031) children -0.026 (0.040) Minority -0.046 (0.036) First Cutpoint -3.285*** (0.118) Second Cutpoint -1.543*** (0.114) Third Cutpoint 0.688*** (0.114)
N 24224 Pseudo-R2 0.051 Log-Likelihood -25,800
* p<0.10, ** p<0.05, *** p<0.01
4 (3) Multilevel Ordered Logistic Model with Varying Intercepts
Using a multilevel ordered logistic regression model with varying intercepts for each country, we find that all variables again match in direction and significance level with the linear model reported in the text. Most importantly, voting is a significant, positive predictor of life satisfaction. As compared to the linear model in the text, however, both of the group-level intercept predictors show up as significant predictors in the multilevel ordered logistic model.
b/se
voted 0.157*** (0.032) male -0.023 (0.025) education 0.108*** (0.030) age -0.027*** (0.005) age*age 0.000*** (0.000) wealth 0.422*** (0.017) income 0.057*** (0.007) married 0.238*** (0.031) children -0.025 (0.039) minority -0.051 (0.035)
loggdppc 0.506*** (0.028) polity2 -0.292*** (0.012)
First Cutpoint -0.197 (0.244) Second Cutpoint 1.546*** (0.243) Third Cutpoint 3.777*** (0.244)
Variance 0.074 Intercepts
N 24,224 Log-Likelihood -25,867 * p<0.10, ** p<0.05, *** p<0.01
5 (4) Figure 1 with Confidence Intervals That Take Into Account the Estimating Error in Both the Fixed and Random Components of the Varying Slope
6 (5) Varying-Slope Model with Time Since Most Recent Election as a Second Slope Predictor
We run the same varying slope model as reported in column (2) of table 1, except including the elapsed number of months since the most recent election as a second slope predictor. The country-level measure of time since the most recent election negatively predicts the individual-level slope on voting, as we would expect if voting leads to happiness with decreasing observability of that impact over time. However, the effect is estimated with great uncertainty and is relatively small in magnitude. The country-level relationship between compulsory voting and the slope on voting remains negative and large relative to the mean value of the voting variable.
(1) All Countries Voted (Mean Slope) 0.13***
(0.033)
Male -0.0080
(0.010)
Education 0.042***
(0.012)
Age -0.011***
(0.0019)
Age*Age 0.00010***
(0.000020)
Wealth 0.17***
(0.0068)
Income 0.018***
(0.0029)
Married 0.092***
(0.012)
Children -0.0059
(0.016)
Minority -0.025*
(0.014) Intercept Predictors
Log(GDP Per Capita) 0.16* (0.084)
Polity Score -0.028
(0.030) Slope Predictors
Enforced Compulsory Voting
-0.066** (0.029) Elapsed Months Since
Election
-0.0010 (0.0010)
Variance of Intercepts 0.045 Variance of Slopes on
Voting
0.0028
Residual Variance 0.57
N 24,224
J 18
Log-Likelihood -27,729
7 (6) Two-Stage Ordered Logistic Regression
We run the two-stage models from table 3 except using an ordered logistic regression as the final model, rather than a linear model. We are not aware of a method for producing correct standard errors in a two-stage ordered logistic regression; therefore, we are providing estimates with uncorrected standard errors. The results are the same as in table 3.
(1) (2) b/se b/se
voted 0.131 0.120 (instrumented) (0.104) (0.164)
male -0.010 0.011 (0.027) (0.040) education 0.102*** 0.081 (0.035) (0.053) age -0.028*** -0.017* (0.006) (0.009) age*age 0.000*** 0.000* (0.000) (0.000) wealth 0.419*** 0.403*** (0.019) (0.027) income 0.051*** 0.040*** (0.008) (0.012) married 0.253*** 0.226*** (0.034) (0.049) children -0.058 -0.002 (0.044) (0.064) minority -0.010 0.050 (0.039) (0.054) First Cutpoint -3.369*** -2.975*** (0.125) (0.171) Second Cutpoint -1.609*** -1.228*** (0.121) (0.164) Third Cutpoint 0.631*** 0.786*** (0.121) (0.163)
N 20780 9509 Pseudo-R2 0.05 0.05 Log-Likeli~d -22,200 -10,100 * p<0.10, ** p<0.05, *** p<0.01
Outcome variable is satisfaction with life. Voted variable
instrumented for in first-stage logistic regressions using voting
eligibility indicator. Standard errors have not been adjusted to
8 (7) Replicating the Results in Other Years of the AmericasBarometer
To see if our results are specific to the 2008 data, we replicate our main results using the
AmericasBarometer data collected by the LAPOP in 2004 and 2006. The main results obtain in all cases – there is a significant negative association between voting and life satisfaction. Several countries were missing either the outcome variable (satisfaction with life) or the key explanatory variable (voting) and are excluded from the analysis. In 2004, all countries were missing the wealth variable, and all countries except for two were missing the minority variable; therefore, we have excluded these predictors from models (1) and (4). In 2006, 12 of 15 countries had data for wealth; therefore, we run the models both with and without this variable. Only five of 15 countries had values for the minority variable, so we have continued to exclude this variable.
(1) (2) (3) (4) (5) (6)
2004 Data Varying Intercepts 2006 Data Varying Intercepts 2006 Data Varying Intercepts 2004 Data Varying Slopes 2006 Data Varying Slopes 2006 Data Varying Slope Individual-Level Predictors
Voted 0.030**
(0.014)
0.065*** (0.014)
0.052*** (0.012)
Voted (Mean Slope) 0.035*
(0.019)
0.065** (0.030)
0.059** (0.027)
Male 0.00069
(0.011) 0.0054 (0.011) 0.022** (0.0094) 0.00080 (0.011) 0.0058 (0.011) 0.023** (0.0094)
Education 0.12***
(0.013) 0.030** (0.012) 0.087*** (0.010) 0.12*** (0.013) 0.030** (0.012) 0.087*** (0.010)
Age -0.010***
(0.0021) -0.011*** (0.0021) -0.012*** (0.0018) -0.0098*** (0.0021) -0.011*** (0.0021) -0.012*** (0.0018)
Age*Age 0.00011***
(0.000023) 0.00012*** (0.000022) 0.00012*** (0.000019) 0.00010*** (0.000023) 0.00012*** (0.000022) 0.00012*** (0.000019)
Wealth 0.17***
(0.0072)
0.17*** (0.0072)
Income 0.017***
(0.0021) 0.0074** (0.0024) 0.023*** (0.0019) 0.017*** (0.0021) 0.0074** (0.0024) 0.023*** (0.0019)
Married 0.095***
(0.014) 0.081*** (0.013) 0.079*** (0.012) 0.095*** (0.014) 0.081*** (0.013) 0.080*** (0.012)
Children -0.056***
(0.014) -0.027 (0.018) -0.028* (0.015) -0.056*** (0.014) -0.026 (0.018) -0.27* (0.015) Country-Level Intercept Predictors
Log(GDP Per Capita) 0.10 (0.10) -0.037 (0.063) 0.023 (0.062) 0.033 (0.095) -0.056 (0.054) -0.0077 (0.053)
Polity Score 0.071
(0.060) -0.048 (0.030) -0.042 (0.031) 0.085 (0.058) -0.047* (0.026) -0.044* (0.027) Country-Level Slope Predictors
Enforced Compulsory Voting -0.0089 (0.027) -0.00070 (0.048) -0.015 (0.040) Variance of Intercepts
0.031 0.019 0.022 0.028 0.013 0.015
Variance of Slopes on Voting
0.00021 0.0043 0.0039
Residual Variance 0.55 0.54 0.54 0.55 0.54 0.53
N 18,104 18,300 25,526 18,104 18,300 25,526
J 10 12 15 10 12 15
Log-Likelihood -20,408 -20,347 -28,319 -20,410 -20,345 -28,315
9 (8) Results Using 2005 Latinobarómetro Data
We replicated the analysis using the 2005 Latinobarómetro data. In neither model is the voting variable a statistically significant predictor of satisfaction with life. In the first model, which estimates a single coefficient for all countries, the variable is negatively signed. In the second model, where the slope is allowed to vary by county, the slope is positively signed in non-compulsory voting countries, and the variable for enforced compulsory voting is a significant, negative predictor of the size of the slope.
(1) (2)
Varying Intercepts
Varying Slopes Individual Level Predictors
Voted -0.010
(0.016) Voted (Mean
Slope)
0.017 (0.019)
Male -0.0090
(0.012)
-0.0090 (0.012)
Education 0.0068***
(0.0017)
0.0069*** (0.0017)
Age -0.011***
(0.0022)
-0.010*** (0.0022)
Age*Age 0.00011***
(0.000023)
0.00010*** (0.000023)
Wealth 0.034***
(0.0038)
0.034*** (0.0038)
Income 0.16***
(0.0080)
0.16*** (0.0080)
Married 0.061***
(0.013)
0.062*** (0.013)
Minority -0.081***
(0.013)
-0.081*** (0.013) Country-Level Intercept Predictors
Log(GDP Per Capita)
0.093 (0.095)
0.098 (0.087)
Polity Score -0.048
(0.059)
-0.041 (0.054) Country-Level Slope Predictors
Enforced
Compulsory Voting
-0.073** (0.030)
Variance of Intercepts
0.065 0.055
Variance of Slopes on Voting
Residual Variance 0.65 0.65
N 17,985 17,985
J 18 18
Log-Likelihood -21,671 -21,671
10 (9) Analysis of a Satisfaction with Life Discontinuity Based on Voting Age
Coefficient estimate on voting eligibility indicator from multivariate regressions with controls for education, married, and children, intended to deal with lack of balance across treated and control groups for data from the youth subset. Regressions that include data from multiple countries also include country-level indicator variables
Data
(Comparison Age Groups)
Unbalanced Variables in Difference in Means Tests (p
< 0.05)
Coefficient on Voting Eligibility Indicator
(Standard Error) All Countries Education, Married, Children -0.004
(0.027) Argentina*
(18 vs. 19)
Children 0.064
(0.174) Bolivia
(18/19 vs 20/21)
Education, Married, Children -0.045 (0.068) Chile
(18/19 vs. 20/21)
Education, Children 0.018 (0.14) Colombia
(18 vs. 20)
- 0.008
(0.154) Costa Rica
(18/19 vs. 20/21)
- 0.044
(0.110) Dominican Republic
(18/20 vs. 22/24)
Married, Children 0.088 (0.106) Ecuador
(18 vs. 20)
Married, Children 0.0167 (0.116) El Salvador
(18/21 vs. 22/25)
Married, Children -0.049 (0.079) Guatemala*
(18 vs. 19)
- -0.043
(0.147) Honduras
(18/19 vs. 21/22)
Married, Children -0.081 (0.126) Mexico
(18 vs. 20)
Married, Children 0.009 (0.135) Nicaragua
(16 vs. 18)
Education 0.027
(0.135) Panama
(18/20 vs. 22/24)
Married, Children -0.100 (0.107) Paraguay
(18-22 vs. 23-27)
Married, Children -0.053 (0.08) Peru
(18/19 vs. 20/21)
Education, Married, Children -0.151 (0.10) Uruguay
(18/20 vs. 22-24)
Education, Married, Children 0.08 (0.11) Venezuela
(18 vs. 19)
Children -0.076
(0.152) Compulsory Voting Countries Education, Married, Children -0.021 (0.037) Non-Compulsory Voting
Countries
Education, Married, Children 0.012 (0.042)
11 (10) Costa Rica Referendum Analysis Using Ordered Logistic Regression
We replicate all four reported linear regressions from the Costa Rica data using ordered logistic models.
In the ordered logistic model corresponding to model (1) in table 4, we see that the coefficient on having voted is positive and statistically significant. In the model corresponding to model (2) in table 4, we see that the coefficient on wanting to vote is positive, statistically significant and larger in magnitude (as compared to the previous model) than the coefficient on voting. In the model corresponding to model (3) in table 4, we see that the coefficient on wanting to vote is positive and marginally significant, while the variable on actually having voted is not statistically significant. The variable on wanting to vote is also larger in magnitude as compared to the coefficient on voting. In the model corresponding to model (4) in table 4, we see that, among the set of people who wanted to vote, the coefficient on having vote is not statistically significant. Other variables generally retain the same sign and levels of
significance.
m1 m2 m3 m4 b/se b/se b/se b/se vote 0.398*** 0.122 0.098 (0.122) (0.189) (0.189) wanting to vote 0.603*** 0.479* (0.205) (0.259) male 0.063 -0.107 -0.095 -0.190 (0.121) (0.140) (0.141) (0.150) education 0.084 -0.008 -0.001 0.074 (0.141) (0.155) (0.156) (0.166) age -0.028 -0.058** -0.059** -0.053** (0.020) (0.024) (0.024) (0.026) age*age 0.000* 0.001*** 0.001*** 0.001** (0.000) (0.000) (0.000) (0.000) wealth 0.336*** 0.408*** 0.401*** 0.385*** (0.076) (0.088) (0.088) (0.094) income 0.071** 0.086** 0.084** 0.087** (0.030) (0.034) (0.034) (0.036) married 0.317** 0.313** 0.302* 0.322* (0.136) (0.156) (0.156) (0.167) children -0.193 -0.148 -0.122 -0.150 (0.178) (0.204) (0.204) (0.218) Minority -0.368* -0.197 -0.196 -0.046 (0.203) (0.238) (0.238) (0.253)
First Cutpoint -2.675*** -2.924*** -2.980*** -3.137*** (0.449) (0.578) (0.582) (0.583) Second Cutpoint -1.211*** -1.339** -1.409** -1.771*** (0.424) (0.546) (0.551) (0.553) Third Cutpoint 0.826* 0.689 0.618 0.237 (0.422) (0.544) (0.548) (0.547)
N 1172 913 908 812
Pseudo-R2 0.033 0.039 0.038 0.032
