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Supplemental Information

Table of Contents

I. Measuring Informality/Formality Status p. SI.1

II. Measurement Validity Checks p. SI.8

III. Question Wordings for Other Variables p. SI.10

IV. Regression Tables p. SI.21

V. Matching Results p. SI.57

VI. LAPOP Vote Choice as Nominal Choice Models p. SI.63

VII. Tables 2 and 3 with Household Wealth as a Covariate p. SI.64

I. Measuring Formality/Informal StatusBelow, we give the questions (and their skipping instructions) used to construct the

informality/formality independent variables used in this paper. We do not report the full set of occupational questions asked in each survey, nor do the question numbers below correspond to their order of appearance in the original questionnaires. They are renumbered here to convey their relative ordering and the logic of the skipping instructions.

A. APES 20151. What do you currently do? Are you ... ? [READ OPTIONS]¿A qué se dedica usted principalmente? ¿Está usted actualmente…? [LEER OPCIONES]

Response options Skipping Instruction How coded

Working Trabajando Continue to 2

Actively looking for work Está buscando trabajo activamente Continue to 2† Unemployed

Student Es estudiante End of battery Non-EAP

Homemaker Se dedica a los quehaceres de su hogar End of battery Non-EAP

Retired or permanently disabled Está jubilado, pensionado o incapacitado permanentemente para trabajar.

Continue to 2† Non-EAP

Not working and not looking for work No trabaja y no está buscando trabajo. End of battery Non-EAP

Don’t know No sabe End of battery Missing

No response No contest End of battery Missing† Coded as unemployed/non-EAP regardless of subsequent answers.

2. In your occupation, are/were you? [READ OPTIONS. IF RETIRED OR UNEMPLOYED, ASK ABOUT MOST RECENT JOB]En su ocupación usted es/fue: [LEER OPCIONES/ SI CONTESTÓ JUBILADO O DESEMPLEADO, PREGUNTAR POR ÚLTIMO EMPLEO]


Employed by the state or a state-owned firmEmpleado del estado o empresa estatal End of battery Formal wage earner

Employed in the private sectorEmpleado en el sector privado Continue to 3

Business owner or partnerDueño o socio de empresa Skip to 4

Own-account (self-employed) worker Trabajador por cuenta propia Skip to 4

SI.1

Worker without payTrabajador no remunerado o sin pago End of battery Informal wage earner

Don’t knowNo sabe End of battery Missing

No responseNo contest End of battery Missing

3. Is there a retirement pension deduction through your job? [READ OPTIONS]¿Por este trabajo tiene descuento jubilatorio? [LEER OPCIONES]


Yes Si End of battery Formal wage earner

No No End of battery Informal wage earner

Don’t know No sabe End of battery Missing

No responseNo contestó End of battery Missing

4. Your business or work activity… [READ OPTIONS]Por su negocio, empresa o actividad: [LEER OPCIONES]


was registered with AFIP once but you no longer make regular payments.Se anotó en la AFIP alguna vez pero luego dejó de hacer pagos regulares

End of battery Informal self-employed worker

was registered with AFIP and you are current with payments. Se anotó en la AFIP y realiza sus pagos regularmente

End of battery Formal business owner

has never been registered with AFIP.No se anotó nunca End of battery Informal self-

employed workerDon’t know. No sabe End of battery Missing

No responseNo contest End of battery Missing

SI.2

B. LAPOP 20061. What is your primary occupation?¿Cuál es su ocupación principal? [No leer alternativas]


Professional, manager Profesional, directive Continue to 2

TechnicianTécnico Continue to 2

Office workerOficinista Continue to 2

Salesperson Comerciante Continue to 2

Farmer Campesino o agricultor Continue to 2

Farmhand Peón agrícola (trabaja la tierra para otros) Continue to 2

Artisan Artesano Continue to 2

Domestic service worker Servicio doméstico Continue to 2

Service (other) worker Otros servicios Continue to 2

Semi-skilled worker (e.g., machine operator)Obrero especializados (operador de maquinaria)

Continue to 2

Unskilled worker Obrero no especializados Continue to 2

Student Estudiante End of battery Non-EAP

Homemaker Ama de casa End of battery Non-EAP

RetireePensionado, jubilado, rentista End of battery Non-EAP

DK/NRNS/NR End of battery Missing

2. Are you currently working?¿Está usted trabajando actualmente?


Yes Si Continue to 3

No No End of battery Non-EAP

No response/Don’t know End of battery Missing

SI.3

No sabe/No contestó

3. In your primary occupation, are you … [Read options]En su ocupación principal usted es: [Leer alternativas]


(1) Employed by the state or a state-owned firm Asalariado del gobierno o empresa estatal?

Continue to 4

(2) Employed in the private sector Asalariado en el sector privado? Continue to 4

(3) Business owner or partner Patrono o socio de empresa? Continue to 4

(4) Own-account (self-employed) worker Trabajador por cuenta propia? Continue to 4

(5) Worker without pay Trabajador no remunerado o sin pago? Continue to 4

Informal wage earner (unless answer to 5 is “yes,” then missing)

No response/Don’t know No sabe/No contestó Continue to 4 Missing

4. In total, how many employees are there in the business where you work? [Read options]¿En total cuántos empleados hay en la empresa o en el lugar donde usted trabaja? [Leer alternativas]


Less than 5 employees Menos de 5 empleados Continue to 5

Informal self-employed (if answer to

3 is 4)5 to 9 employees De 5 a 9 empleados Continue to 5 Missing (if answer to 3

is 3) 10 to 19 employees De 10 a 19 empleados Continue to 5 Formal business owner

(if answer to 3 is 3)20 to 100 employees De 20 a 100 empleados Continue to 5 Formal business owner

(if answer to 3 is 3)More than 100 employees Más de 100 empleados Continue to 5 Formal business owner

(if answer to 3 is 3)No response/Don’t know No sabe/No contestó Continue to 5 Missing

5. Do you have social security?¿Tiene usted seguro social? 1

SI.4


Yes Si End of battery Formal wage earner (if

answer to 3 is 1, 2 or 4)No No End of battery Informal wage earner (if

answer to 3 is 1 or 2)No response/Don’t know No sabe/No contestó End of battery Missing

C. LAPOP 20081. How do you mainly spend your time? Are you currently… [Read options]¿A qué se dedica usted principalmente? ¿Está usted actualmente: [Leer alternativas]


Working Trabajando Continue to 2

Not working, but have a job No está trabajando en este momento pero tiene trabajo

Continue to 2

Actively looking for work Está buscando trabajo activamente End of battery Unemployed

Student Es estudiante End of battery Non-EAP

Homemaker Se dedica a los quehaceres de su hogar End of battery Non-EAP

Retired or permanently disabled Está jubilado, pensionado o incapacitado permanentemente para trabajar.

End of battery Non-EAP

Not working and not looking for work No trabaja y no está buscando trabajo. End of battery Non-EAP

Don’t know/ No response NS/NR End of battery Missing

2. In your primary occupation, are you … [Read options]En su ocupación principal usted es: [Leer alternativas]


(1) Employed by the state or a state-owned firm Asalariado del gobierno o empresa estatal?

Continue to 3

1 This question was not asked in Bolivia, Argentina, Ecuador, or Brazil, so 2006 respondents

from these countries are dropped from all analyses.

SI.5

(2) Employed in the private sector Asalariado en el sector privado? Continue to 3

(3) Business owner or partner Patrono o socio de empresa? Continue to 3 Missing (can’t tell if

businesses are formal)

(4) Own-account (self-employed) worker Trabajador por cuenta propia? Continue to 3

Informal self-employed (if answer

to 3 is 2)(5) Worker without pay Trabajador no remunerado o sin pago? Continue to 3

Informal wage earner (unless answer to 3 is “yes,” then missing)

No response/Don’t know No sabe/No contestó Continue to 3 Missing

3. Do you have health insurance or social security through your employer?¿Tiene usted seguro de salud o seguro social a través de su empresa o su empleador?2


Yes Sí End of battery Formal wage earner (if

answer to 2 is 1, 2, or 4)

2 This is the wording used in Bolivia, Brazil, El Salvador, and Nicaragua.

Panama asked only about social security: “¿Tiene seguro social a traves de su empresa o

empleador?”

Argentina, Guatemala, Honduras, Colombia, Ecuador, Peru, Chile, and Dominican Republic

asked only about health insurance: “¿Tiene seguro de salud a traves de su empresa o

empleador?”

Mexico: “¿Tiene accesso a la seguridad social a traves de su trabajo y cuenta con prestaciones,

como el derecho a recibir atencion medica en los hospitales de gobierno, como el Seguro, el

ISSSTE, o tiene accesso a los hopitales del gobierno en su localidad, u hospitales”

Uruguay: “¿Esta usted registrado en el BPS (esta en caja) atraves de su empresa o empleador”

Paraguay: “¿Tiene seguro de salud privado o IPS Instituto de Prevision Social a traves de su

empresa o su empleador?”

Costa Rica: “¿Esta usted asegurado/a a la CCSS a traves de su empresa o su empleador?”

SI.6

NoNo End of battery Informal wage earner (if

answer to 2 is 1 or 2)No response/Don’t know No sabe/No contestó End of battery Missing

D. BEPS 20141. What do you currently do? Are you ... ? [READ OPTIONS]A o que o(a) Sr.(a) se dedica atualmente? O(A) Sr.(a) [LEIA ALTERNATIVAS]


Employed or self-employed.Trabalha como empregado ou por conta própria

Continue to 2

Actively looking for work Está procurando emprego ativamente? End of battery Unemployed

Student É estudante? End of battery Non-EAP

HomemakerSe dedica aos afazeres de sua casa? End of battery Non-EAP

Retired É aposentado(a)? End of battery Non-EAP

Not working and not looking for workNão trabalha e não está procurando emprego?

End of battery Non-EAP

Don’t knowNão sabe End of battery Missing

No responseNão respondeu End of battery Missing

2. For your current job, do you have either a signed workers booklet or a civil service contract? No seu trabalho atual, o(a) Sr.(a) tem carteira de trabalho assinada ou é estatutário?


Yes Sim End of battery Formal worker

No Não End of battery Informal worker

Don’t know Não sabe End of battery Missing

SI.7

No responseNão respondeu End of battery Missing

E. Brazilian Four-City Survey, 1999 1. Do you have a job or are you not working right now?O(a) senhor(a) tem emprego ou não trabalha no momento? Response options Instruction How codedYes, have a job Sim, tenho emprego. Go to 3

No, not working.Não, não trabalho Go to 2

Don’t know/No responseNS/NR End battery Missing

2. Are you looking for work, are you a student, retired, homemaker, or what?O(A) senhor(a) esta procurando emprego, é estudante, é aposentado, é dona de casa ou que?Response options Instruction How codedLooking Procurando End of battery Unemployed

Student Estudante End of battery Non-EAP

Retiree Aposentado End of battery Non-EAP

Homemaker Dona de casa End of battery Non-EAP

OtherOutro Go to 3

Don’t know/No responseNS/NR End battery Missing

3. Do you have a signed workers booklet?

O(a) senhor(a) tem carteira de trabalho assinada?

Response options Instruction How codedYes Sim End of battery Formal worker

No Não Go to 4 Informal worker (if

answer to 4 is “no”)Don’t know/No responseNS/NR End of battery Missing

SI.8

4. Are you a civil servant?O(a) senhor(a) é funcionário público? Response options Instruction How codedYesSim End of battery Formal worker

No Não End of battery Informal worker (if

answer to 3 is “no”)Don’t know/No responseNS/NR End of battery Missing

II. Measurement Validity ChecksWe conducted a convergent validity check (i.e., whether it is correlated with alternative

measures of informality) by calculating the correlation between the share of workers that were informal according to our definition using LAPOP (at the country-year level) and the share according to the social protection definition as measured in household surveys.3 By their compilers' own admission, one should not consider these household survey figures to be the true or gold standard figures, but it is reassuring that the correlation between our LAPOP-based measures and theirs is .76 (N=23 country years).

To gauge the criterion-related validity (i.e., whether it is correlated with conceptually distinct factors that are known correlates of informality) of the LAPOP measure, we consider its relationship with age. Using household surveys, Perry et al. (2007, p. 53) find that the probability of informality status evolves with the life cycle in a somewhat complex way that is surprisingly similar across countries. First, the probability of being an informal wage earner (“Informal WE”) peaks in youth (i.e., late teens) and then declines linearly with age thereafter. Second, the probability of being a formal wage earner (“Formal WE”) is concave with respect to age, with its peak occurring somewhere between 20 and 40. Finally, the probability of being an informal self-employed worker (“Informal SE”) peaks the latest—somewhere between 40 and 50—rising steadily up until that point. Figure SI.1 reports the probability of holding each status against age in the LAPOP data, and it shows that these exact same patterns obtain.

Figure SI.1: Probability of Informality/Formality Status by AgePanel A: LAPOP 2006

3 Centro de Estudios Distributivos, Laborales, y Sociales [CEDLAS] (2016). Socio-Economic

Database for Latin America and the Caribbean. http://sedlac.econo.unlp.edu.ar/esp/. Consulted

on November 2, 2016.

SI.9

http://sedlac.econo.unlp.edu.ar/esp/

Panel B: LAPOP 2008

III. Question Wordings for Other VariablesA. APES 2015

VoteFor which candidate did you vote in the presidential election of October 25? [RECORD SPONTANEOUS ANSWER. IF CAN’T REMEMBER, READ OPTIONS AND RECORD.] (1 in MNL, 8.35 in OLS) Daniel Scioli. (2 in MNL, 16.4 in OLS) Mauricio Macri. (3 in MNL, 11.6 in OLS) Sergio Massa. (. in MNL, 7.9 in OLS) Margarita

SI.10

Stolbizer. (. in MNL, 16.73 in OLS) Adolfo Rodríguez Saá. (. in MNL, 5.7 in OLS) Nicolás Del Caño. (rest are . in both) [NO LEER] Other. [NO LEER] Voted blank or annulled. [NO LEER] Didn’t vote. No recuerda. No contesta.¿Y a qué candidato votó en las elecciones presidenciales del 25 de octubre? [REGISTRAR RESPUESTA ESPONTÁNEA. SI NO RECUERDA, LEER OPCIONES Y REGISTRAR. RESPUESTA ÚNICA] Daniel Scioli. Mauricio Macri. Sergio Massa. Margarita Stolbizer. Adolfo Rodríguez Saá. Nicolás Del Caño. [NO LEER] Otro. [NO LEER] Votó en blanco/nulo. [NO LEER] No votó. No recuerda. No contesta.

Turnout(1) Answer of some candidate’s name to above question. (0) Answer of “voted blank or annulled” or “didn’t vote” to above question.

PartisanshipIndependently of which party you voted for in the last election or will vote for in the one that is coming, do you sympathize with a particular political party? (1) Yes. (0) No. (.) DK/NR.Independientemente de por cuál partido votó en la elección pasada o votará en la que viene, en general, ¿simpatiza usted con algún partido político en particular? (1) Sí. (0) No. (.) NS/NC

Participation in Orgs. (Respondent’s score is the maximum across answers to four different questions about four different types of groups.)

Now I’m going to read a list of groups and organization. Please tell me if you attend meetings of these organizations (4) at least once per week. (3) one or two times per month. (2) one or two times per year. (1) Never. Neighborhood meetings. Professional association meetings. Labor union meetings. Meetings of a party or political movements. Ahora voy a leerle una lista de grupos y organizaciones. Por favor, dígame si usted asiste a las reuniones de estas organizaciones: (4) por lo menos una vez a la semana, (3) una o dos veces al mes, (2) una o dos veces al año, o (1) nunca. Reuniones de vecinos. Reuniones de una asociación de profesionales. Reuniones de un sindicato. Reuniones de un partido o movimiento político.

Support for AUHNow I’m going to ask you about some public policies. I’m going to ask that in each case, you tell me if you (5) strongly agree, (4) somewhat agree, (3) neither agree nor disagree, (2) somewhat disagree, or (1) strongly disagree. How much do you agree with ... [SHOW CARD WITH AGREEMENT LEVELS] the Universal Child Allowance.Ahora le voy a preguntar sobre políticas públicas. Le voy a pedir que en cada caso me diga si usted está (5) muy de acuerdo, (4) algo de acuerdo, (3) ni de acuerdo ni en desacuerdo, (2) algo en desacuerdo o (1) muy en desacuerdo. ¿Cuán de acuerdo está usted con … [MOSTRAR TARJETA DE NIVEL DE ACUERDO]. La Asignación Universal por Hijo

Programa familias versus ANSESNow let’s talk about social policies. Do you want the government to raise benefits for Programa Familias, which is given to the poor, or do you want the government to raise

SI.11

benefits for ANSES, which benefits only formal sector workers? Or do you not want the government to raise social spending? (1) Programa familias. (2) ANSES. (3) Not raise social spending [Neither].Hablando de los planes sociales, ¿prefiere usted que el gobierno aumente los beneficios del Programa Familias, que se da a los pobres, o prefiere que aumente los beneficios de la ANSES, que beneficia sólo a los trabajadores formales? ¿O prefiere que el gobierno no aumente el gasto social? (1) Programa familias. (2) ANSES. (3) Not raise social spending [Neither]. (.) NS/NR.

EducationWhat is the maximum level of education you have reached? (0) Without formal education or incomplete primary. (1) Complete primary. (2) Incomplete secondary. (3) Complete secondary. (4) Incomplete tertiary or university. (5) Complete tertiary or university. (.) DK/NR. ¿Cuál es el máximo nivel educativo alcanzado por usted? (0) Sin instrucción o primario incompleto. (1) Primario completo. (2) Secundario incompleto. (3) Secundario completo. (4) Terciario o universitario incompleto. (5) Terciario o universitario completo. (.) NS/NC.

Woman(0) Man. (1) Woman. [Interview mark without asking] (0) Hombre. (1) Mujer. [Marcar sin preguntar]

Urbanicity(0) Dwells in city with <100,000 residents. (1) Dwells in city with >100,000 residents [Interviewer mark without asking] (0) <100,000. (1) >100,000. [Marcar sin preguntar]

Household Wealth (Index created by survey administrators from the following ten items)Could you tell me if you have in your house (1) Refrigerator with freezer [1=yes, 0=no, else=.]. (2) Landline [1=yes, 0=no, else=.]. (3) Cell phone [1=yes, 0=no, else=.]. (4) Car [1=yes, 0=no, else=.]. (5) Washing machine [1=yes, 0=no, else=.]. (6) Motorcycle [1=yes, 0=no, else=.]. (7) Computer [1=yes, 0=no, else=.]. (8) Internet service [1=yes, 0=no, else=.]. (9) Flat screen television [1=yes, 0=no, else=.]. (10) Gas hookup [1=yes, 0=no, else=.].

¿Podría decirme cuáles de los siguientes objetos tiene en el hogar? (1) Heledera con freezer [1=tiene, 0=no tiene, NS/NC=.]. (2) Teléfono convencional/fijo/residencial [1=tiene, 0=no tiene, NS/NC=.]. (3) Teléfono celular [1=tiene, 0=no tiene, NS/NC=.]. (4) Auto [1=tiene, 0=no tiene, NS/NC=.]. (5) Lavarropas [1=tiene, 0=no tiene, NS/NC=.]. (6) Moto [1=tiene, 0=no tiene, NS/NC=.]. (7) Computadora [1=tiene, 0=no tiene, NS/NC=.]. (8) Servicio de Internet [1=tiene, 0=no tiene, NS/NC=.]. (9) Televisor de pantalla plana [1=tiene, 0=no tiene, NS/NC=.]. (10) Gas de red [1=tiene, 0=no tiene, NS/NC=.].

B. LAPOP

SI.12

Political participation index (This is an additive index created by Boulding and Holzner 2016. It is the sum of the following eight binary items)

There are people who work for some party or candidate during electoral campaigns. Did you work for any candidate or party in the last presidential elections of 2002? (1) Yes, worked (0) Did not work (.) DK/DRHay personas que trabajan por algún partido político o candidato durante las campañas electorales. ¿Trabajo usted para algún candidato o partido en las pasadas elecciones presidenciales del 2002? (1) Si trabajo (0) No trabajo (.) NS/NR

During last year, did you participate in a public demonstration or protest? Did you do it sometimes, almost never or never? (1) Sometimes (1) Almost Never (0) Never (.) DK/DR. ¿En el último año, ha participado en una manifestación o protesta pública? ¿Lo ha hecho algunas veces, casi nunca o nunca? (1) Algunas veces (1) Casi Nunca (0) Nunca (.) NS/NR

Have you attended a town hall meeting or other meeting convened by the mayor in the past 12 months? (1) Yes (0) No (.) DK/DR¿Ha asistido a un cabildo abierto o una sesión municipal durante los últimos 12 meses? (1) Si (0) No (.) NS/NR

Have you sought help from or presented a request to any office, official, or council man of the municipality in the past 12 months? (1) Yes (0) No (.) DK/DR¿Ha solicitado ayuda o ha presentado una petición a alguna oficina, funcionario, concejal o sindico de la municipalidad durante los últimos 12 meses? (1) Si (0) No (.) NS/NR

Now, to speak of something else, sometimes people and communities have problems that they cannot resolve by themselves, and to resolve them they ask for help from an official or government office. In order to solve your problems have you ever requested help or cooperation from . . . ? Ahora, para hablar de otra cosa, a veces la gente y las comunidades tienen problemas que no pueden resolver por sí mismas, y para poder resolverlos piden ayuda a algún funcionario u oficina del gobierno ¿Para poder resolver sus problemas alguna vez ha pedido usted ayuda o cooperación . .?

Any local authorities (mayor, municipality, perfect)? (1) Yes (0) No (.) DK/DRA alguna autoridad local (alcalde, municipalidad, prefecto, intendente). (1) Si (0) No (.) NS/NR

Any ministry, public institution or state agency? (1) Yes (0) No (.) DK/DRA algún ministerio/secretario, institución publica, u oficina del estado. (1) Si (0) No (.) NS/NR

A deputy of Congress? (1) Yes (0) No (.) DK/DRA algún diputado del Congreso. (1) Si (0) No (.) NS/NR

Now I am going to read a list of groups and organizations. Please tell me if you attend their meetings at least once a week, one or twice a month, once or twice a year, or never. [Repeat “once a week,” “once or twice a month,” “once or twice a year,” or “never” to help the respondent. Meetings of a political party or political organization? You attended them (1) Once a week (1) Once or twice a week (0) Once or twice a year (0) Never (.) DK

SI.13

Ahora le voy a leer una lista de grupos y organizaciones. Por favor, dígame si usted asiste a reuniones de ellos por lo menos una vez a la semana, una o dos veces al mes, una o dos veces al año, o nunca [Repetir “una vez a la semana,” “una o dos veces al mes,” “una o dos veces al año”, o “nunca” para ayudar el entrevistado] ¿reuniones de un partido o movimiento político? Asiste. . . (1) Una vez a la semana (1) Una o dos veces al mes (0) Una o dos veces al año (0) Nunca (.) NS/NR

TurnoutDid you vote in the last presidential elections? (1) Voted (0) Did not vote (.) DK/DR ¿Voto usted en las últimas elecciones presidenciales? (1) Si Voto (0) No voto (.) NS/NR

PartisanshipDo you currently identify with a political party? (1) Yes (0) No (.) DK ¿En este momento, simpatiza con algún partido político? (1) Si (0) No (.) NS/NR

Participation in Organizations (This is an index created by Boulding and Holzner 2016. The value is the maximum across these four items)

Now I am going to read out a list of groups and organizations. Please tell me if you attend their meetings (4) at least once a week, (3) once or twice a month, (2) once or twice a year, or (1) never. [Repeat “once a week,” “once or twice a month,” “once or twice a year,” or “never” to help the respondent]Ahora le voy a leer una lista de groups y organizaciones. Por favor, digame si usted asiste a reuniones de ellos (4) por lo menos una vez a la semana, (3) una o dos veces al mes, (2) una o dos veces al año, o (1) nunca [Repetir “una vez a la semana,” “una o dos veces al mes,” “una o dos veces al año”, o “nunca” para ayudar el entrevistado]

The meetings of a parents association at school? ¿De una asociación de padres de familia de la escuela o colegio?

The meetings of a committee or council for community improvement? ¿Un comité o junta de mejoras para la comunidad?

The meetings of an association of professionals, traders, or farmers? ¿De una asociación de profesionales, comerciantes, productores, y/o organizaciones campesinas?

Associations or groups of women or home makers. [Women Only, 2008 only] ¿Reuniones de asociaciones o grupos de mujeres o amas de casa?

Vote ChoiceFor which candidate did you vote for President in the last presidential elections? (.) No one (voted but left ballot blank or annulled their vote). (W-B score) Insert names and parties. (.) DK/NR (.) N/A (did not vote)¿Por quién voto para presidente en las últimas elecciones presidenciales? (.) Ninguna (fue a votar pero dejo boleta en blanco, o anulo su voto. (W-B score) Insertar nombre de candidato y nombre del partido o alianza. (.) NS/NR. (.)Inap (no voto)

SI.14

Market policy attitudes (We ran a principal components analysis on the polychoric correlation matrix for the following four ítems. We use the first factor score.) (2008 only)

Now, let’s use a similar scale, but the number 1 represents “strongly disagree” and the number 7 represents “strongly agree.” A number between 1 and 7 represents an intermediate score.Ahora, vamos a usar una escalera similar, pero el número 1 representa “muy en desacuerdo” y el número 7 representa “muy de acuerdo”. Un número entre el 1 y el 7, representa un puntaje intermedio.

The state, and not the private sector, should own the most important businesses and industries in the country. How much do you agree or disagree with this statement?El Estado (gentilicio), en lugar del sector privado, debería ser el dueño de las empresas e industrias más importantes del país. ¿Hasta qué punto está de acuerdo o en desacuerdo con esta frase?

The state, and not individuals, should be primarily responsible to ensure people’s well-being. How much do you agree or disagree with this statement?El Estado (gentilicio), más que los individuos, debería ser el principal responsable de asegurar el bienestar de la gente. ¿Hasta qué punto está de acuerdo o en desacuerdo con esta frase?

The state, and not private business, should be primarily responsible for creating jobs. How much do you agree or disagree with this statement?El Estado (gentilicio), más que la empresa privada, debería ser el principal responsable de crear empleos. ¿Hasta qué punto está de acuerdo o en desacuerdo con esta frase?

The state should implement strong policies to reduce income inequality between rich and poor. How much do you agree or disagree with this statement?El Estado (gentilicio) debe implementar políticas firmes para reducir la desigualdad de ingresos entre ricos y pobres. ¿Hasta qué punto está de acuerdo o en desacuerdo con esta frase?

EducationWhat was the last year of education you passed? (0) none (1-6) Primary education (7-12) Secondary education (13-18+) University (.) DK/DR¿Cuál fue el último año de enseñanza que usted aprobó? (0) Ninguno. (1-6) Educación primaria. (7-12) Educación secundaria. (13-18+) Universitaria. (.) NS/NR

WomanSex [note down; do not ask]: (0) Male (1) FemaleGénero [anotar, no pregunte]: (0) Hombre) (1) Mujer

AgeHow old are you?¿Cuál es su edad en años cumplidos?

Urbanicity(5) National capital. (4) Large city. (3) Mid-sized city. (2) Small city. (1) Rural area. (.) NR/NA.(5) Capital nacional (área metropolitana). (4) Ciudad grande. (3) Ciudad mediana. (2) Ciudad pequeña. (1) Área rural. (.) NR/N/A.

SI.15

Household Wealth (We ran a principal components analysis on the polychoric correlation matrix for the following eleven ítems. We use the first factor score.) (2006 and 2008)

To end, could you tell me if you have the following in your house: [read out all items] (1) Television Set [1 = Yes, 0 = No, else =.]. (2) Refrigerator [1 = Yes, 0 = No, else =.]. (3) Landline [1 = Yes, 0 = No, else =.]. (4) Cellular Telephone [1 = Yes, 0 = No, else =.]. (5) Vehicle. How many? [3 = Three or more, 2 = Two, 1 = One, 0 = None, else =.]. (6) Washing Machine [1 = Yes, 0 = No, else =.]. (7) Microwave oven [1 = Yes, 0 = No, else =.]. (8) Motorcycle [1 = Yes, 0 = No, else =.]. (9) Drinking water indoors [1 = Yes, 0 = No, else =.]. (10) Indoor Bathroom [1 = Yes, 0 = No, else =.]. (11) Computer [1 = Yes, 0 = No, else =.].Para finalizar, podría decirme si en su casa tienen: [leer todos] (1) Televisor [1 = Si, 2 = No, NS/NR=.]. (2) Refrigeradora (nevera) [1 = Si, 2 = No, NS/NR=.]. (3) Teléfono convencional (no celular) [1 = Si, 2 = No, NS/NR=.]. (4) Teléfono Celular [1 = Si, 2 = No, NS/NR=.]. (5) Vehículo. Cuantos? [3 = Tres o mas, 2 = Dos, 1 = Uno, 0 = Ninguno, NS/NR =.]. (6) Lavadora de ropa [1 = Si, 2 = No, NS/NR=.]. (7) Microondas [1 = Si, 2 = No, NS/NR=.]. (8) Motocicleta [1 = Si, 2 = No, NS/NR=.]. (9) Agua potable dentro de la casa [1 = Si, 2 = No, NS/NR=.]. (10) Cuarto de baño dentro de la casa [1 = Si, 2 = No, NS/NR=.]. (11) Computadora [1 = Si, 2 = No, NS/NR=.].

C. BEPS 2014Turnout

Let’s talk a little about the elections that occurred on Sunday, October 6. Did you vote in those elections? (1) Yes [unless subsequently said annulled or voted blank in “vote choice” variable, then 0]. (0) No. (.) DK/NS.Vamos falar um pouco sobre as eleições que se realizaram no domingo, dia 5 de outubro. O Sr.(a) votou nestas eleições? (1) Sim (0) Não (.) NS/NR

PartisanshipDo you currently sympathize with a political party? (1) Yes. (0) No.Atualmente o(a) Sr.(a) simpatiza com algum partido político? Sim ou não? (1) Sim (0) Não (.) NS/NR

Vote ChoiceFor whom did you vote for president of the Republic? [Order of candidate options was randomized.] (1 in MNL, 6.37 in OLS) Dilma Rousseff. (2 in MNL, 13.46 in OLS) Aécio Neves. (4 in MNL, 7.5 in OLS) Marina Silva. (. in MNL, 15.62 in OLS) Pastor Everaldo Pereira, (. in MNL, 7.36 in OLS) Eduardo Jorge, (. in MNL, 7.36 in OLS) Luciana Genro, (.) Another candidate, (.) Spoiled my ballot, (.) Voted blank, (.) DK/NR.Em quem o(a) Sr.(a) votou para presidente da república [Ler as opções]? [randomizar a ordem dos nomes dos candidatos] Dilma Rousseff. Aécio Neves. Marina Silva. Pastor Everaldo Pereira. Eduardo Jorge. Luciana Genro. Algum outro candidato. Anulou o voto. Votou em branco. NS/NR

Vote Stability

SI.16

(Based on “vote choice” variable above. Limited to respondents who had a candidate preference in both of waves 4/5 and 6 [note that participants responded in either wave 4 or 5, but not both]. 0=changed candidates between the two waves, 1=chose same candidate in both waves.)

Means-test Index. (We ran a principal components analysis on the polychoric correlation matrix for the following five ítems. We use the first factor score.)

Do you approve or disapprove of income transfer programs like Family Grant that make monthly payments to poor families? (1) Approve. (0) Disapprove. (.) DK/NR.O(a) Sr.(a) aprova ou desaprova programas de transferência de renda como o Bolsa Família que fazem pagamentos mensais às famílias pobres? (1) Aprova. (0) Desaprova (.) NS/NR

Do you approve or disapprove of programs like More Doctors that bring foreign doctors to work in Brazil. (1) Approve. (0) Disapprove. (.) DK/NR.O(a) Sr.(a) aprova ou desaprova programas como o Mais Médicos, que traz médicos estrangeiros para trabalhar no Brasil? (1) Aprova. (0) Desaprova (.) NS/NR

Do you approve or disapprove of programs like My House My Life that finance the purchase of homes for low- and middle-income families? (1) Approve. (0) Disapprove. (.) DK/NR. O(a) Sr.(a) aprova ou desaprova programas como o Minha Casa Minha Vida que financiam a compra de casas por famílias de renda baixa e média? (1) Aprova. (0) Desaprova (.) NS/NR.

Do you approve or disapprove of programs like Social Charge for Electricity that give discounts on electricity bills to low income families? (1) Approve. (0) Disapprove. (.) DK/NR. O(a) Sr.(a) aprova ou desaprova programas como a Tarifa Social de Energia Elétrica, que dá descontos na conta de luz para famílias de renda baixa? (1) Aprova. (0) Desaprova (.) NS/NR

Do you approve or disapprove of programs like Continuous Cash Benefit, which make monthly payments to the elderly and disabled of low income? (1) Approve. (0) Disapprove. (.) DK/NR.O(a) Sr.(a) aprova ou desaprova programas como o Benefício de Prestação Continuado, que faz pagamentos mensais a idosos e pessoas incapacitadas de trabalhar de baixa renda? (1) Aprova. (0) Desaprova (.) NS/NR

Bolsa Familia versus INSS Now let’s talk about social policies. Some types of programs, like Bolsa Família (Family Grant), use resources from taxes paid by everybody to benefit some people of low income. Other types of programs, like the INSS, use resources from taxes paid by those with a signed workers booklet and benefit only those who pay. Which type of policy do you prefer? (1) Policies that benefits some with taxes paid by everyone, like the Bolsa Familia (Family Grant). (2) Policies that benefit those who pay, like the INSS. (3) Both or indifference or neither [Not read].Agora, falando sobre políticas sociais. Alguns tipos de programas como o Bolsa Família usam recursos de impostos pagos por todos para beneficiar algumas pessoas de baixa renda; outros tipos de programas, como o INSS, usam recursos de impostos pagos somente

SI.17

por aqueles que têm carteira assinada e só beneficiam quem paga. Qual destes tipos de política o(a) Sr.(a) prefere: (1) Políticas que beneficiam alguns com recursos pagos por todos, como o Bolsa Família. (2) Políticas que só beneficiam aqueles que pagam, como o INSS. (3) Ambas (NÃO LER)

EducationWhat was the last year of schooling that you completed? (1) Pre-school, literacy course for children. (2) Literacy course for youth and adults. (3/4) Elementary (old system). (5) Kindergarten to 2nd grade. (6) 3rd grade. (7) 4th to 7th grade. (8) Elementary school supplementary education. (9) Middle school (old system). (10) Regular or supplementary middle school. (11) University. (12) Vocational training. (13) Masters. (14) Doctorate. (.) DK/NR. Qual foi o último ano de escola que o(a) Sr.(a) terminou? (1) Creche, pré-escolar (maternal e jardim de infância), classe de alfabetização – CA. (2) Alfabetização de jovens e adultos. (3) Antigo primário (elementar). (4) Antigo ginásio (médio 1º ciclo). (5) Ensino fundamental ou 1º grau (da 1ª a 3ª série/ do 1º ao 4º ano). (6) Ensino fundamental ou 1º grau (4ª série/ 5º ano). (7) Ensino fundamental ou 1º grau (da 5ª a 8ª série/ 6º ao 9º ano). (8) Supletivo do ensino fundamental ou do 1º grau. (9) Antigo científico, clássico, etc.....(médio 2º ciclo). (10) Regular ou supletivo do ensino médio ou do 2º grau. (11) Superior de graduação. (12) Especialização de nível superior ( mínimo de 360 horas ). (13) Mestrado. (14) Doutorado. (.) NS/NR

Woman(0) Man. (1) Woman. [Interview mark without asking] (0) Homem. (1) Mulher. [Marcar sem perguntar]

AgeWhat is your age? [Write down number. DK/NR=.]Qual é a sua idade? [Escrever número. NS/NR=.]

Urbanicity(0) Rural. (1) Urban. [Interview mark without asking] (0) Rural. (1) Urbano. [Marcar sem perguntar]

Household Wealth (Index created by survey administrators from the following seven items)Could you tell me if you have in your house (1) TV [1=yes, 0=no, else=.]. (2) Refrigerator [1=yes, 0=no, else=.]. (3) Landline [1=yes, 0=no, else=.]. (4) Cell phone [1=yes, 0=no, else=.]. (5) Car [1=yes, 0=no, else=.]. (6) Computer [1=yes, 0=no, else=.]. (7) How many bathroom are there in your house, including that of the domestic help?Poderia dizer-me se em sua casa tem: (1) TV [1=sim, 0=não, NS/NR=.]. (2) Refrigerador [1=sim, 0=não, NS/NR=.]. (3) Telefone fixo [1=sim, 0=não, NS/NR=.]. (4) Telefone celular [1=sim, 0=não, NS/NR=.]. (5) Carro [1=sim, 0=não, NS/NR=.]. (6) Computador [1=sim, 0=não, NS/NR=.]. (7) Quantos banheiros tem na casa, incluindo dependência de empregada?

D. Brazilian Four-City Survey, 1999

SI.18

Vote ChoiceFor whom did you vote for President of the Republic last year? (1 in MNL, 10.38 in OLS) Ciro Gomes. (2 in MNL, 8.15 in OLS) Luiz Inácio Lula da Silva. (3 in MNL, 13.46 in OLS) Fernando Henrique Cardoso. (.) Enéas Carneiro. (.) Outros candidatos (NÃO LER ESTE ÍTEM). (.) Nenhum/Não votou. (.) NS/NR.Em quem o(a) sr.(a) votou para Presidente da República no ano passado? Ciro Gomes. Luiz Inácio Lula da Silva. Fernando Henrique Cardoso. Enéas Carneiro. Outros candidatos (NÃO LER ESTE ÍTEM). Nenhum/Não votou. NS/NR.

Market policy attitudes. (We ran a principal components analysis on the polychoric correlation matrix for the following three ítems. We use the first factor score.)

In the last ten/fifteen years, many state-owned businesses, which were directed by the state, were sold to the private sector in a process called ‘privatization.’ People have different opinions about privatization. Are you in favor, against or do not have an opinion on privatization? Are you strongly or slightly (in favor/against)? (5) Strongly in favor. (4) Somewhat in favor. (3) No opinion, depends. (2) Somewhat against. (1) Strong against. (.) DK/NR.Nos últimos quinze anos, muitas empresas estatais, que eram dirigidas pelo Estado, foram vendidas para a iniciativa privada, num processo chamado de privatização. As pessoas têm diferentes opiniões sobre a privatização. O(a) senhor(a) é a favor, contra, ou não tem opinião sobre essa política de privatização? (ENTREVISTADOR: SE “A FAVOR”...) É fortemente a favor, ou só um pouco a favor? (ENTREVISTADOR: SE “CONTRA”...) É fortemente contra, ou só um pouco contra? (5) Fortemente a favor. (4) Um pouco a favor. (3) Não tem opinião, Depende. (2) Um pouco contra. (1) Fortemente contra. (.) NS/NR

In the last ten/fifteen years, Brazil’s trade with foreign countries grew. This increase in trade is known as ‘trade opening.’ Some people favor and others oppose this ‘trade opening.’ Are you in favor, against, or do you not have an opinion on trade opening? Are you strongly or slightly (in favor/against)? (5) Strongly in favor. (4) Somewhat in favor. (3) No opinion, depends. (2) Somewhat against. (1) Strong against. (.) DK/NR. Nos últimos quinze anos, o comércio do Brasil com países estrangeiros aumentou. Este aumento no comércio é conhecido como abertura econômica ou abertura comercial. Algumas pessoas são favoráveis e outras são contra a abertura comercial. O(a) senhor(a) é a favor, contra, ou não tem opinião sobre essa política de abertura comercial? (ENTREVISTADOR: SE A FAVOR....) É fortemente a favor, ou só um pouco a favor? (ENTREVISTADOR: SE CONTRA....) É fortemente contra, ou só um pouco contra? (5) Fortemente a favor. (4) Um pouco a favor. (3) Não tem opinião, Depende. (2) Um pouco contra. (1) Fortemente contra. (.) NS/NR

Much has been said about foreign businesses investing in Brazil, which has grown over the last ten/fifteen years. Are you in favor, against, or do you not have an opinion on this growth in foreign investment in Brazil? Are you strongly or slightly (in favor/against)? (5) Strongly in favor. (4) Somewhat in favor. (3) No opinion, depends. (2) Somewhat against. (1) Strong against. (.) DK/NR.Muito se tem falado sobre os investimentos de empresas estrangeiras no Brasil, que cresceu nos últimos anos. O(a) senhor(a) é a favor, contra, ou não tem opinião sobre o crescimento do investimento estrangeiro no Brasil? (ENTREVISTADOR: SE A FAVOR....) É fortemente a favor, ou só um pouco a favor? (ENTREVISTADOR: SE CONTRA....) É

SI.19

fortemente contra, ou só um pouco contra? (5) Fortemente a favor. (4) Um pouco a favor. (3) Não tem opinião, Depende. (2) Um pouco contra. (1) Fortemente contra. (.) NS/NR

EducationWhat is your education level? (1) No instruction. (2) Kindergartern or 1st grade (or equivalent). (3) 2nd or 3rd grade (or equivalent). (4) 4th or 5th grade (or equivalent). (5) 6th or 7th grade (or equivalent). (6) Secondary incomplete. (7) Secondary complete. (8) Tertiary incomplete. (9) Tertiary complete. (10) Graduate.Qual o seu grau de instrução/escolaridade? (1) Sem instrução. (2) 1ª a 2ª série (ou equivalente). (3) 3ª a 4ª série (ou eqivalente). (4) 5ª a 6ª série (ou equivalente). (5) 7ª a 8ª série (ou equivalente). (6) Segundo grau (incompleto). (7) Segundo grau (completo). (8) Superior (incompleto). (9) Superior (completo). (10) Pos-graduação.

Woman(0) Man. (1) Woman. [Interview mark without asking] (0) Homem. (1) Mulher. [Marcar sem perguntar]

AgeWhat is your age? [Write down number. DK/NR=.]Qual é a sua idade? [Escrever número. NS/NR=.]

SI.20

IV. Regression TablesA. Figure 1

Table SI.1A: The Impact of Informality on Participation: Neg. Bin. Models for Figure 1 (top panel)Mexico Guatemala El Salv. Honduras Nicaragua Costa Rica Panama Colombia Ecuador

DV: Political Participation IndexFormal Wage Earner

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

Informal 0.183*(0.088)

-0.046(0.107)

0.103(0.081)

0.127(0.099)

-0.014(0.097)

-0.044(0.093)

-0.216*(0.105)

0.111(0.101)

-0.272*(0.113)

Formal Employer -0.484(0.294)

0.780(0.832)

-1.428*(0.540)

-15.474*(1.004)

-0.236(0.467)

0.090(0.404)

0.868(0.494)

-1.204(0.927)

Non-EAP and Unemployed

0.089(0.089)

-0.390*(0.115)

-0.097(0.079)

-0.280*(0.102)

-0.254*(0.094)

-0.102(0.071)

-0.246*(0.085)

-0.145(0.091)

-0.365*(0.119)

Education 0.026*(0.008)

0.038*(0.009)

0.041*(0.006)

0.041*(0.008)

0.054*(0.007)

0.034*(0.007)

0.023*(0.009)

0.064*(0.009)

0.065*(0.011)

Woman -0.036(0.070)

-0.146(0.077)

-0.296*(0.055)

0.091(0.070)

-0.279*(0.064)

-0.041(0.064)

-0.095(0.072)

-0.170*(0.075)

-0.148(0.088)

Age (logged) 0.553*(0.086)

0.310*(0.094)

0.293*(0.066)

0.592*(0.081)

0.308*(0.070)

0.478*(0.071)

0.316*(0.089)

0.526*(0.099)

0.231*(0.109)

Urbanicity -0.012(0.021)

-0.099*(0.026)

-0.068*(0.018)

-0.109*(0.024)

-0.117*(0.020)

-0.015(0.018)

-0.000(0.021)

-0.241*(0.035)

-0.115*(0.028)

2008 -0.139*(0.061)

0.296*(0.071)

-0.093(0.051)

-0.315*(0.059)

0.091(0.058)

-0.319*(0.060)

-0.110(0.067)

0.311*(0.072)

0.000(.)

Constant -2.455*(0.355)

-1.554*(0.378)

-1.191*(0.270)

-2.214*(0.323)

-1.284*(0.293)

-2.075*(0.282)

-1.524*(0.366)

-2.223*(0.411)

-1.442*(0.453)

lnalphaConstant 0.494*

(0.060)0.332*(0.085)

-0.072(0.068)

0.128(0.068)

0.205*(0.066)

0.000(0.078)

0.486*(0.068)

0.262*(0.085)

0.410*(0.093)

Observations 2843 2449 3200 2912 3008 2832 2804 2360 2561Standard errors in parentheses* p<0.05

SI.21

Table SI.1B: The Impact of Informality on Participation: Neg. Bin. Models for Figure 1 (top panel)Bolivia Peru Paraguay Chile Uruguay Brazil Venezuela Argentina DR


0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

Informal -0.229*(0.090)

-0.060(0.078)

0.016(0.140)

0.163(0.139)

-0.147(0.081)

0.283*(0.137)

0.016(0.092)

-0.075(0.102)

-0.136(0.077)

Formal Employer -1.065*(0.517)

0.527(0.350)

-0.360(0.476)


-0.393*(0.096)

-0.162*(0.079)

-0.296(0.158)

0.001(0.123)

-0.137*(0.067)

0.077(0.140)

-0.074(0.081)

-0.196(0.101)

-0.160*(0.077)

Education 0.038*(0.007)

0.049*(0.007)

0.089*(0.014)

0.013(0.014)

0.041*(0.007)

0.024*(0.011)

0.030*(0.008)

-0.001(0.011)

0.015*(0.006)

Woman -0.341*(0.069)

-0.198*(0.056)

-0.191(0.109)

0.162(0.104)

0.059(0.059)

-0.049(0.085)

0.121(0.062)

-0.038(0.081)

-0.199*(0.054)

Age (logged) 0.362*(0.089)

0.497*(0.068)

0.253(0.145)

0.254*(0.123)

0.266*(0.072)

0.188(0.110)

0.520*(0.086)

0.057(0.106)

0.185*(0.064)

Urbanicity -0.138*(0.023)

-0.216*(0.017)

-0.113*(0.039)

-0.049(0.032)

0.005(0.021)

-0.137*(0.030)

-0.026(0.033)

-0.131*(0.035)

-0.101*(0.015)

2008 0.000(.)

-0.239*(0.053)

0.000(.)

0.000(.)

-0.056(0.056)

0.000(.)

-0.247*(0.063)

0.000(.)

-0.037(0.049)

Constant -1.035*(0.368)

-1.484*(0.301)

-1.584*(0.610)

-1.517*(0.541)

-1.403*(0.296)

-0.725(0.465)

-2.117*(0.361)

0.296(0.437)

-0.160(0.274)

lnalphaConstant -0.394*

(0.104)-0.306*(0.085)

0.215(0.116)

0.475*(0.094)

-0.117(0.075)

0.094(0.101)

0.396*(0.059)

0.019(0.099)

-0.141*(0.064)


SI.22

Table SI.1C: The Impact of Informality on Participation: Neg. Bin. Models for Figure 1 (top panel)Region


0.000(.)

Informal 0.010(0.033)



-0.146*(0.028)

Education 0.038*(0.004)

Woman -0.103*(0.036)

Age (logged) 0.370*(0.036)


2008 -0.090(0.053)

Constant -1.516*(0.173)


(0.067)var(_cons[pais])Constant 0.032*

(0.010)Observations 43707Standard errors in parentheses* p<0.05

SI.23

Table SI.1D: The Impact of Informality on Participation: Neg. Bin. Models for Figure 1 (bottom panel)Mexico Guatemala El Salv. Honduras Nicaragua Costa Rica Panama Colombia Ecuador


0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

Informal Wage Earner

0.211(0.124)

-0.216(0.135)

0.060(0.106)

-0.022(0.123)

-0.233(0.133)

-0.204(0.141)

-0.155(0.164)

0.160(0.123)

-0.076(0.145)

Informal Self-Employed

0.171(0.095)

0.042(0.112)

0.123(0.086)

0.192(0.103)

0.055(0.100)

0.049(0.110)

-0.233*(0.116)

-0.087(0.096)

-0.390*(0.119)


0.777(0.825)

-1.427*(0.540)

-15.853*(1.004)

-0.233(0.466)

0.092(0.405)

0.866(0.494)

-1.224(0.930)


0.089(0.089)

-0.383*(0.116)

-0.097(0.079)

-0.281*(0.102)

-0.256*(0.094)

-0.105(0.071)

-0.246*(0.085)

-0.145(0.090)

-0.365*(0.119)

Education 0.025*(0.008)

0.040*(0.009)

0.040*(0.006)

0.041*(0.008)

0.054*(0.007)

0.033*(0.007)

0.023*(0.009)

0.066*(0.008)

0.063*(0.011)

Woman -0.037(0.070)

-0.142(0.077)

-0.297*(0.055)

0.096(0.070)

-0.275*(0.064)

-0.036(0.065)

-0.096(0.072)

-0.117(0.068)

-0.161(0.087)

Age (logged) 0.555*(0.087)

0.290*(0.094)

0.288*(0.067)

0.581*(0.081)

0.295*(0.070)

0.465*(0.071)

0.317*(0.089)

0.565*(0.093)

0.253*(0.108)

Urbanicity 0.011(0.021)

0.099*(0.026)

0.067*(0.018)

0.109*(0.024)

0.116*(0.020)

0.016(0.018)

0.001(0.021)

0.261*(0.033)

0.120*(0.027)

2008 -0.140*(0.061)

0.309*(0.071)

-0.093(0.051)

-0.318*(0.059)

0.098(0.058)

-0.315*(0.060)

-0.112(0.068)

0.231*(0.067)

0.000(.)

Constant -2.526*(0.377)

-2.109*(0.413)

-1.577*(0.294)

-2.837*(0.365)

-1.942*(0.310)

-2.119*(0.305)

-1.529*(0.374)

-3.879*(0.404)

-2.200*(0.490)


(0.060)0.323*(0.086)

-0.072(0.068)

0.123(0.068)

0.195*(0.067)

-0.003(0.078)

0.486*(0.068)

0.226*(0.078)

0.399*(0.093)


SI.24

Table SI.1E: The Impact of Informality on Participation: Neg. Bin. Models for Figure 1 (bottom panel)Bolivia Peru Paraguay Chile Uruguay Brazil Venezuela Argentina DR


0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)


-0.182(0.115)

0.004(0.112)

-0.001(0.167)

-0.137(0.192)

-0.172(0.121)

0.306*(0.151)

0.039(0.116)

-0.046(0.134)

-0.121(0.092)


-0.252*(0.095)

-0.085(0.082)

0.029(0.153)

0.408*(0.160)

-0.131(0.097)

0.265(0.151)

0.000(0.106)

-0.104(0.121)

-0.147(0.084)


0.527(0.350)

-0.362(0.476)


-0.393*(0.096)

-0.164*(0.079)

-0.295(0.158)

0.008(0.123)

-0.137*(0.067)

0.075(0.140)

-0.074(0.081)

-0.196(0.101)

-0.161*(0.077)

Education 0.038*(0.007)

0.048*(0.007)

0.089*(0.014)

0.013(0.014)

0.041*(0.007)

0.024*(0.011)

0.030*(0.008)

-0.002(0.011)

0.015*(0.006)

Woman -0.341*(0.069)

-0.202*(0.056)

-0.189(0.110)

0.157(0.104)

0.060(0.059)

-0.052(0.086)

0.120(0.062)

-0.041(0.083)

-0.201*(0.055)

Age (logged) 0.369*(0.089)

0.503*(0.068)

0.249(0.148)

0.212(0.123)

0.264*(0.073)

0.190(0.110)

0.521*(0.086)

0.060(0.106)

0.187*(0.064)

Urbanicity 0.138*(0.023)

0.217*(0.016)

0.113*(0.039)

0.047(0.032)

-0.005(0.021)

0.137*(0.030)

0.025(0.033)

0.131*(0.035)

0.102*(0.015)

2008 0.000(.)

-0.241*(0.052)

0.000(.)

0.000(.)

-0.056(0.056)

0.000(.)

-0.247*(0.063)

0.000(.)

-0.038(0.049)

Constant -1.883*(0.400)

-2.788*(0.316)

-2.256*(0.652)

-1.651*(0.563)

-1.364*(0.305)

-1.552*(0.477)

-2.270*(0.375)

-0.495(0.432)

-0.773*(0.277)

lnalphaConstant -0.396*

(0.105)-0.308*(0.085)

0.216(0.116)

0.455*(0.096)

-0.117(0.075)

0.093(0.101)

0.395*(0.059)

0.018(0.099)

-0.141*(0.064)


SI.25

Table SI.1F: The Impact of Informality on Participation: Neg. Bin. Models for Figure 1 (bottom panel)Region


0.000(.)


-0.014(0.035)


0.023(0.039)



-0.146*(0.028)

Education 0.039*(0.004)

Woman -0.099*(0.035)

Age (logged) 0.371*(0.037)


2008 -0.089(0.052)

Constant -2.033*(0.195)




SI.26

B. Figure 2Table SI.2A: The Impact of Informality on Turnout: Probit Models for Figure 2 (top panel)

Mexico Guatemala El Salv. Honduras Nicaragua Costa Rica Panama Colombia EcuadorDV: TurnoutFormal Wage Earner

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

Informal -0.040(0.079)

-0.082(0.096)

-0.022(0.081)

-0.195(0.107)

-0.180(0.104)

-0.263*(0.080)

-0.254*(0.096)

-0.131(0.081)

-0.085(0.156)

Formal Employer 0.300(0.446)

0.312(0.674)

-0.133(0.508)

0.101(0.443)

-0.358(0.381)

0.000(.)

0.721(0.687)


-0.299*(0.078)

-0.641*(0.096)

-0.243*(0.076)

-0.676*(0.101)

-0.548*(0.099)

-0.237*(0.062)

-0.750*(0.078)

-0.140*(0.069)

-0.550*(0.154)

Education 0.041*(0.008)

0.048*(0.007)

0.047*(0.006)

0.038*(0.008)

0.049*(0.007)

0.059*(0.007)

0.057*(0.008)

0.065*(0.007)

0.071*(0.012)

Woman 0.295*(0.064)

-0.129*(0.057)

0.113*(0.053)

0.203*(0.065)

0.116*(0.053)

0.163*(0.056)

0.280*(0.059)

0.026(0.057)

0.261*(0.090)

Age (logged) 1.627*(0.085)

0.894*(0.074)

1.322*(0.072)

1.297*(0.078)

1.134*(0.065)

0.791*(0.065)

1.428*(0.081)

1.182*(0.076)

0.630*(0.126)


-0.025(0.018)

-0.019(0.017)

-0.021(0.021)

-0.023(0.017)

-0.006(0.016)

-0.101*(0.018)

-0.162*(0.024)

-0.021(0.028)

2008 0.034(0.053)

0.432*(0.052)

-0.024(0.049)

-0.499*(0.055)

0.309*(0.049)

-0.052(0.051)

-0.385*(0.055)

0.155*(0.055)

0.000(.)

Constant -5.426*(0.338)

-2.801*(0.294)

-4.403*(0.283)

-3.492*(0.310)

-3.584*(0.274)

-2.703*(0.261)

-4.023*(0.332)

-3.924*(0.302)

-1.387*(0.545)


SI.27

Table SI.2B: The Impact of Informality on Turnout: Probit Models for Figure 2 (top panel)Bolivia Peru Paraguay Chile Uruguay Brazil Venezuela Argentina DR

DV: TurnoutFormal Wage Earner

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

Informal -0.062(0.124)

-0.108(0.144)

-0.305*(0.111)

-0.086(0.121)

-0.630*(0.119)

-0.147(0.159)

0.037(0.085)

-0.103(0.110)

-0.211*(0.099)

Formal Employer 0.000(.)

0.000(.)

0.000(.)


-0.280*(0.123)

-0.501*(0.144)

-0.620*(0.118)

-0.217*(0.104)

-0.887*(0.112)

-0.471*(0.155)

-0.107(0.077)

-0.566*(0.099)

-0.522*(0.098)

Education 0.074*(0.009)

0.092*(0.011)

0.055*(0.009)

0.045*(0.013)

0.053*(0.014)

0.055*(0.013)

0.057*(0.008)

0.053*(0.010)

0.028*(0.008)

Woman 0.038(0.073)

0.262*(0.077)

-0.026(0.079)

0.054(0.093)

0.312*(0.090)

0.113(0.089)

0.072(0.058)

0.016(0.081)

0.212*(0.066)

Age (logged) 1.856*(0.112)

1.381*(0.129)

1.986*(0.117)

2.627*(0.143)

2.131*(0.140)

0.439*(0.122)

1.098*(0.084)

0.264*(0.099)

1.399*(0.095)


-0.028(0.022)

-0.017(0.022)

-0.021(0.028)

-0.007(0.032)

-0.137*(0.031)

0.023(0.030)

-0.077(0.039)

-0.052*(0.018)

2008 0.000(.)

-0.194*(0.070)

0.030(0.067)

0.000(.)

-0.093(0.081)

0.000(.)

0.164*(0.058)

0.000(.)

-0.222*(0.060)

Constant -6.305*(0.463)

-4.081*(0.530)

-6.504*(0.465)

-9.363*(0.598)

-6.309*(0.539)

-0.223(0.498)

-3.745*(0.352)

-0.181(0.425)

-3.883*(0.378)


SI.28

Table SI.2C: The Impact of Informality on Turnout: Probit Models for Figure 2 (top panel)Region


0.000(.)

Informal -0.091*(0.039)



-0.409*(0.062)

Education 0.051*(0.003)

Woman 0.125*(0.031)

Age (logged) 1.266*(0.102)


2008 -0.008(0.074)

Constant -3.903*(0.360)

var(_cons[pais])Constant 0.088*


SI.29

Table SI.2D: The Impact of Informality on Turnout: Probit Models for Figure 2 (bottom panel)Mexico Guatemala El Salv. Honduras Nicaragua Costa Rica Panama Colombia Ecuador


0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)


-0.031(0.108)

-0.096(0.111)

-0.024(0.104)

-0.298*(0.126)

-0.298*(0.124)

-0.358*(0.110)

-0.114(0.157)

-0.071(0.098)

-0.245(0.178)


-0.044(0.086)

-0.073(0.102)

-0.021(0.088)

-0.145(0.113)

-0.130(0.108)

-0.187(0.099)

-0.296*(0.103)

-0.126(0.077)

0.009(0.167)


0.312(0.674)

-0.133(0.508)

0.103(0.443)

-0.356(0.381)

0.000(.)

0.709(0.685)


-0.298*(0.078)

-0.640*(0.096)

-0.243*(0.076)

-0.678*(0.101)

-0.549*(0.099)

-0.238*(0.062)

-0.752*(0.078)

-0.159*(0.068)

-0.553*(0.154)

Education 0.041*(0.008)

0.048*(0.007)

0.047*(0.006)

0.038*(0.008)

0.049*(0.007)

0.058*(0.007)

0.056*(0.008)

0.061*(0.007)

0.071*(0.012)

Woman 0.295*(0.064)

-0.129*(0.057)

0.113*(0.053)

0.207*(0.065)

0.121*(0.053)

0.165*(0.056)

0.279*(0.059)

0.031(0.052)

0.269*(0.089)

Age (logged) 1.627*(0.085)

0.892*(0.074)

1.322*(0.072)

1.291*(0.078)

1.125*(0.065)

0.781*(0.065)

1.432*(0.081)

1.179*(0.071)

0.613*(0.126)


0.025(0.018)

0.018(0.017)

0.021(0.021)

0.023(0.017)

0.006(0.016)

0.102*(0.018)

0.176*(0.023)

0.019(0.028)

2008 0.034(0.053)

0.433*(0.053)

-0.024(0.049)

-0.502*(0.055)

0.313*(0.049)

-0.047(0.051)

-0.389*(0.055)

0.184*(0.051)

0.000(.)

Constant -5.525*(0.355)

-2.951*(0.320)

-4.513*(0.306)

-3.593*(0.339)

-3.702*(0.289)

-2.706*(0.281)

-4.633*(0.340)

-4.902*(0.307)

-1.450*(0.568)


SI.30

Table SI.2E: The Impact of Informality on Turnout: Probit Models for Figure 2 (bottom panel)Bolivia Peru Paraguay Chile Uruguay Brazil Venezuela Argentina DR


0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)


-0.068(0.143)

-0.283(0.165)

-0.425*(0.131)

-0.068(0.146)

-0.673*(0.136)

-0.235(0.181)

-0.057(0.103)

0.122(0.145)

-0.227*(0.113)


-0.059(0.131)

-0.024(0.151)

-0.240*(0.117)

-0.108(0.163)

-0.591*(0.151)

-0.077(0.174)

0.105(0.099)

-0.292*(0.129)

-0.199(0.111)

Formal Employer 0.000(.)

0.000(.)

0.000(.)


-0.280*(0.123)

-0.499*(0.144)

-0.618*(0.118)

-0.217*(0.104)

-0.887*(0.112)

-0.466*(0.155)

-0.108(0.077)

-0.564*(0.098)

-0.523*(0.098)

Education 0.074*(0.009)

0.093*(0.011)

0.057*(0.009)

0.045*(0.013)

0.053*(0.014)

0.056*(0.013)

0.057*(0.008)

0.051*(0.010)

0.028*(0.008)

Woman 0.039(0.073)

0.273*(0.077)

-0.015(0.079)

0.054(0.093)

0.313*(0.090)

0.116(0.090)

0.076(0.058)

-0.007(0.082)

0.214*(0.066)

Age (logged) 1.855*(0.113)

1.362*(0.129)

1.966*(0.118)

2.630*(0.144)

2.123*(0.140)

0.430*(0.122)

1.093*(0.084)

0.284*(0.099)

1.396*(0.095)


0.025(0.022)

0.014(0.022)

0.021(0.028)

0.008(0.032)

0.137*(0.031)

-0.022(0.030)

0.078*(0.039)

0.052*(0.018)

2008 0.000(.)

-0.187*(0.070)

0.033(0.067)

0.000(.)

-0.093(0.081)

0.000(.)

0.164*(0.058)

0.000(.)

-0.222*(0.060)

Constant -6.399*(0.486)

-4.206*(0.540)

-6.552*(0.483)

-9.498*(0.602)

-6.325*(0.551)

-1.024*(0.513)

-3.598*(0.347)

-0.680(0.406)

-4.189*(0.381)


SI.31

Table SI.2F: The Impact of Informality on Turnout: Probit Models for Figure 2 (bottom panel)Region


0.000(.)


-0.136*(0.049)


-0.062(0.036)



-0.409*(0.061)

Education 0.051*(0.003)

Woman 0.127*(0.031)

Age (logged) 1.260*(0.100)


2008 -0.005(0.073)

Constant -4.114*(0.354)



SI.32

C. Figure 3Table SI.3A: The Impact of Informality on Partisanship: Probit Models for Figure 3 (top panel)

Mexico Guatemala El Salv. Honduras Nicaragua Costa Rica Panama Colombia EcuadorDV: PartisanshipFormal Wage Earner

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

Informal -0.070(0.069)

-0.029(0.096)

-0.008(0.074)

-0.151(0.084)

-0.004(0.086)

-0.174*(0.080)

-0.166*(0.079)

-0.176*(0.084)

-0.024(0.100)


-0.012(0.681)

0.000(.)

0.000(.)

0.082(0.414)

-0.703(0.452)

0.095(0.763)

-0.484(0.644)


-0.212*(0.068)

-0.214*(0.101)

-0.062(0.069)

-0.373*(0.082)

-0.177*(0.082)

-0.054(0.059)

-0.337*(0.065)

0.049(0.070)

-0.054(0.103)

Education 0.021*(0.006)

0.043*(0.007)

0.038*(0.006)

0.040*(0.007)

0.030*(0.006)

0.018*(0.006)

0.011(0.007)

0.049*(0.007)

0.028*(0.009)

Woman 0.036(0.055)

-0.115(0.065)

-0.181*(0.050)

0.008(0.056)

-0.189*(0.049)

-0.213*(0.054)

0.011(0.054)

-0.292*(0.059)

-0.155*(0.071)

Age (logged) 0.480*(0.067)

0.206*(0.079)

0.333*(0.061)

0.668*(0.065)

0.532*(0.056)

0.556*(0.062)

0.324*(0.068)

0.832*(0.077)

0.325*(0.087)


-0.039(0.021)

0.067*(0.016)

-0.019(0.018)

-0.063*(0.016)

0.012(0.015)

-0.024(0.016)

-0.077*(0.026)

-0.037(0.023)

2008 -0.498*(0.047)

0.038(0.060)

0.226*(0.046)

0.149*(0.047)

-0.260*(0.046)

-0.161*(0.050)

0.332*(0.051)

-0.038(0.057)

0.000(.)

Constant -1.560*(0.275)

-1.809*(0.315)

-2.038*(0.247)

-2.508*(0.262)

-1.714*(0.237)

-2.401*(0.247)

-1.795*(0.290)

-3.582*(0.312)

-2.113*(0.375)


SI.33

Table SI.3B: The Impact of Informality on Partisanship: Probit Models for Figure 3 (top panel)Bolivia Peru Paraguay Chile Uruguay Brazil Venezuela Argentina DR

DV: PartisanshipFormal Wage Earner

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

Informal -0.177(0.094)

-0.036(0.080)

0.012(0.119)

-0.157(0.110)

-0.057(0.074)

-0.034(0.118)

-0.078(0.074)

-0.076(0.099)

-0.094(0.078)


-0.578(0.465)

-0.822(0.762)


-0.268*(0.098)

-0.041(0.081)

-0.092(0.126)

-0.246*(0.098)

-0.012(0.061)

-0.129(0.118)

-0.079(0.067)

-0.056(0.096)

-0.056(0.077)

Education -0.023*(0.007)

0.022*(0.007)

0.012(0.011)

0.052*(0.011)

0.031*(0.007)

0.028*(0.010)

0.023*(0.007)

-0.000(0.010)

0.003(0.006)

Woman -0.196*(0.066)

-0.231*(0.055)

-0.088(0.088)

-0.106(0.083)

-0.164*(0.053)

-0.138(0.077)

-0.138*(0.052)

-0.161*(0.079)

-0.025(0.053)

Age (logged) 0.320*(0.082)

0.404*(0.070)

0.621*(0.116)

0.627*(0.108)

0.550*(0.062)

0.182(0.098)

0.523*(0.069)

0.326*(0.099)

0.158*(0.064)


-0.045*(0.016)

-0.047(0.028)

0.027(0.028)

0.038(0.019)

-0.004(0.027)

-0.009(0.027)

-0.097*(0.036)

-0.055*(0.015)

2008 0.000(.)

-0.359*(0.052)

0.000(.)

0.000(.)

-0.088(0.050)

0.000(.)

-0.005(0.051)

0.000(.)

0.252*(0.049)

Constant -1.066*(0.339)

-1.933*(0.309)

-1.865*(0.476)

-3.559*(0.474)

-2.275*(0.259)

-1.378*(0.402)

-2.382*(0.289)

-1.369*(0.407)

-0.065(0.265)


SI.34

Table SI.3C: The Impact of Informality on Partisanship: Probit Models for Figure 3 (top panel)Region


0.000(.)

Informal -0.072*(0.019)



-0.123*(0.031)

Education 0.025*(0.004)

Woman -0.127*(0.024)

Age (logged) 0.455*(0.042)


2008 -0.041(0.074)

Constant -2.039*(0.195)



SI.35

Table SI.3D: The Impact of Informality on Partisanship: Probit Models for Figure 3 (bottom panel)Mexico Guatemala El Salv. Honduras Nicaragua Costa Rica Panama Colombia Ecuador


0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)


-0.140(0.097)

-0.124(0.116)

-0.149(0.099)

-0.311*(0.103)

-0.121(0.108)

-0.393*(0.122)

-0.050(0.135)

-0.168(0.105)

0.130(0.121)


-0.040(0.075)

0.024(0.102)

0.060(0.080)

-0.077(0.088)

0.041(0.089)

-0.043(0.097)

-0.200*(0.086)

-0.042(0.077)

-0.109(0.108)


-0.011(0.680)

0.000(.)

0.000(.)

0.084(0.415)

-0.701(0.451)

0.091(0.763)

-0.468(0.639)


-0.212*(0.068)

-0.209*(0.101)

-0.060(0.069)

-0.376*(0.082)

-0.176*(0.082)

-0.056(0.059)

-0.338*(0.065)

0.034(0.069)

-0.055(0.103)

Education 0.021*(0.006)

0.044*(0.008)

0.038*(0.006)

0.040*(0.007)

0.031*(0.006)

0.017*(0.006)

0.011(0.007)

0.048*(0.007)

0.027*(0.009)

Woman 0.038(0.055)

-0.113(0.065)

-0.183*(0.050)

0.013(0.056)

-0.186*(0.049)

-0.208*(0.055)

0.010(0.054)

-0.300*(0.054)

-0.161*(0.071)

Age (logged) 0.476*(0.067)

0.195*(0.080)

0.316*(0.061)

0.654*(0.065)

0.524*(0.056)

0.540*(0.062)

0.328*(0.069)

0.828*(0.072)

0.343*(0.087)


0.039(0.021)

-0.069*(0.016)

0.019(0.018)

0.063*(0.016)

-0.012(0.015)

0.025(0.016)

0.089*(0.024)

0.040(0.023)

2008 -0.497*(0.047)

0.045(0.060)

0.227*(0.046)

0.143*(0.047)

-0.256*(0.046)

-0.154*(0.050)

0.328*(0.051)

0.028(0.052)

0.000(.)

Constant -2.022*(0.292)

-2.022*(0.345)

-1.569*(0.269)

-2.573*(0.287)

-2.068*(0.253)

-2.274*(0.268)

-1.954*(0.293)

-4.068*(0.316)

-2.399*(0.391)


SI.36

Table SI.3E: The Impact of Informality on Partisanship: Probit Models for Figure 3 (bottom panel)Bolivia Peru Paraguay Chile Uruguay Brazil Venezuela Argentina DR


0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)


-0.050(0.118)

-0.003(0.107)

-0.007(0.143)

-0.303*(0.141)

-0.171(0.107)

-0.043(0.139)

0.027(0.094)

0.072(0.122)

0.004(0.092)


-0.236*(0.099)

-0.049(0.084)

0.023(0.129)

-0.018(0.139)

0.013(0.088)

-0.028(0.130)

-0.151(0.085)

-0.236(0.128)

-0.168(0.086)


-0.575(0.465)

-0.834(0.763)


-0.267*(0.098)

-0.042(0.081)

-0.092(0.126)

-0.242*(0.097)

-0.011(0.061)

-0.129(0.118)

-0.078(0.067)

-0.055(0.096)

-0.054(0.077)

Education -0.023*(0.007)

0.022*(0.007)

0.012(0.011)

0.052*(0.011)

0.031*(0.007)

0.028*(0.010)

0.023*(0.007)

-0.001(0.010)

0.002(0.006)

Woman -0.197*(0.066)

-0.232*(0.055)

-0.086(0.088)

-0.106(0.083)

-0.162*(0.053)

-0.137(0.077)

-0.144*(0.052)

-0.176*(0.080)

-0.038(0.054)

Age (logged) 0.341*(0.082)

0.408*(0.070)

0.617*(0.117)

0.609*(0.108)

0.540*(0.063)

0.181(0.098)

0.527*(0.069)

0.344*(0.100)

0.171*(0.064)


0.045*(0.016)

0.047(0.028)

-0.029(0.028)

-0.037(0.019)

0.004(0.027)

0.008(0.027)

0.101*(0.036)

0.057*(0.015)

2008 0.000(.)

-0.360*(0.052)

0.000(.)

0.000(.)

-0.087(0.050)

0.000(.)

-0.004(0.051)

0.000(.)

0.251*(0.049)

Constant -1.379*(0.367)

-2.210*(0.317)

-2.136*(0.502)

-3.333*(0.479)

-2.012*(0.271)

-1.397*(0.422)

-2.440*(0.295)

-2.006*(0.413)

-0.432(0.270)


SI.37

Table SI.3F: The Impact of Informality on Partisanship: Probit Models for Figure 3 (bottom panel)Region


0.000(.)


-0.099*(0.027)


-0.050(0.027)



-0.121*(0.031)

Education 0.025*(0.004)

Woman -0.128*(0.024)

Age (logged) 0.455*(0.042)


2008 -0.036(0.073)

Constant -2.175*(0.180)



SI.38

D. Figure 4Table SI.4A: The Impact of Informality on Participation in Organizations: Ordered Probit Models for Figure 4 (top panel)

Mexico Guatemala El Salv. Honduras Nicaragua Costa Rica Panama Colombia EcuadorDV: Organizational ParticipationFormal Wage Earner

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

Informal 0.047(0.059)

0.090(0.071)

0.008(0.065)

0.021(0.070)

0.125(0.071)

-0.116(0.069)

-0.089(0.069)

-0.071(0.067)

-0.117(0.071)


-0.979(0.582)

-0.485(0.431)

-4.692*(0.229)

-0.435(0.394)

0.120(0.276)

0.523(0.676)

0.586*(0.212)


-0.173*(0.059)

-0.202*(0.073)

-0.208*(0.063)

-0.346*(0.071)

-0.158*(0.069)

-0.200*(0.052)

-0.283*(0.055)

-0.263*(0.059)

-0.456*(0.077)

Education 0.003(0.006)

0.017*(0.005)

0.012*(0.005)

0.015*(0.006)

0.018*(0.005)

0.021*(0.005)

0.011(0.006)

0.022*(0.006)

0.028*(0.007)

Woman 0.393*(0.049)

0.186*(0.048)

0.195*(0.045)

0.402*(0.051)

0.271*(0.044)

0.348*(0.048)

0.369*(0.046)

0.348*(0.049)

0.449*(0.054)

Age (logged) 0.131*(0.061)

0.338*(0.059)

0.232*(0.057)

0.580*(0.059)

0.319*(0.050)

0.259*(0.056)

0.213*(0.057)

0.193*(0.063)

0.193*(0.071)


-0.052*(0.015)

-0.067*(0.014)

-0.053*(0.016)

-0.053*(0.014)

-0.054*(0.014)

-0.055*(0.014)

-0.057*(0.021)

-0.008(0.017)

2008 -0.121*(0.041)

0.246*(0.043)

0.003(0.040)

-0.286*(0.042)

0.062(0.040)

0.259*(0.043)

-0.221*(0.043)

-0.034(0.047)

0.000(.)


SI.39

Table SI.4B: The Impact of Informality on Participation in Organizations: Models for Figure 4 (top panel)Bolivia Peru Paraguay Chile Uruguay Brazil Venezuela Argentina DR

DV: Organizational ParticipationFormal Wage Earner

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

Informal -0.067(0.073)

0.067(0.062)

-0.159*(0.075)

0.063(0.087)

-0.010(0.063)

0.144(0.105)

-0.014(0.061)

-0.057(0.082)

-0.080(0.063)


0.134(0.305)

0.930(0.574)


-0.458*(0.077)

-0.197*(0.064)

-0.297*(0.082)

-0.155*(0.076)

-0.263*(0.056)

-0.207*(0.104)

-0.238*(0.056)

-0.235*(0.077)

-0.255*(0.063)


0.017*(0.005)

0.026*(0.006)

0.024*(0.009)

0.033*(0.006)

0.024*(0.008)

0.008(0.006)

0.006(0.008)

0.028*(0.005)

Woman 0.286*(0.053)

0.301*(0.043)

0.169*(0.058)

0.661*(0.067)

0.366*(0.048)

0.445*(0.064)

0.345*(0.044)

0.358*(0.066)

0.192*(0.046)

Age (logged) 0.405*(0.071)

0.315*(0.058)

0.561*(0.076)

0.145(0.084)

-0.100(0.058)

0.281*(0.085)

0.469*(0.061)

0.537*(0.081)

0.148*(0.057)


-0.085*(0.013)

-0.108*(0.017)

-0.087*(0.021)

-0.053*(0.017)

-0.068*(0.022)

0.007(0.022)

-0.082*(0.028)

-0.060*(0.012)

2008 0.000(.)

-0.232*(0.040)

0.167*(0.049)

0.000(.)

0.095*(0.046)

0.000(.)

-0.148*(0.042)

0.000(.)

0.062(0.041)


SI.40

Table SI.4C: The Impact of Informality on Participation in Organizations: Ordered Probit Models for Figure 4 (top panel)Region


0.000(.)

Informal 0.003(0.019)



-0.253*(0.019)

Education 0.017*(0.002)

Woman 0.323*(0.023)

Age (logged) 0.278*(0.044)


2008 -0.015(0.050)



SI.41

Table SI.4D: The Impact of Informality on Participation in Organizations: Ordered Probit Models for Figure 4 (bottom panel)Mexico Guatemala El Salv. Honduras Nicaragua Costa Rica Panama Colombia Ecuador


0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)


0.177*(0.082)

-0.039(0.087)

0.008(0.087)

-0.145(0.088)

-0.197*(0.093)

-0.199*(0.101)

0.093(0.125)

-0.033(0.083)

-0.131(0.088)


-0.012(0.065)

0.159*(0.075)

0.008(0.069)

0.093(0.073)

0.242*(0.074)

-0.057(0.083)

-0.139(0.074)

-0.088(0.062)

-0.109(0.077)


-0.979(0.580)

-0.485(0.431)

-4.697*(0.229)

-0.430(0.395)

0.122(0.277)

0.517(0.675)

0.594*(0.220)


-0.172*(0.059)

-0.196*(0.074)

-0.208*(0.063)

-0.349*(0.071)

-0.158*(0.069)

-0.201*(0.052)

-0.285*(0.055)

-0.251*(0.058)

-0.456*(0.077)


0.019*(0.005)

0.012*(0.005)

0.015*(0.006)

0.019*(0.005)

0.021*(0.005)

0.011(0.006)

0.024*(0.005)

0.028*(0.007)

Woman 0.389*(0.049)

0.188*(0.048)

0.195*(0.045)

0.408*(0.051)

0.282*(0.044)

0.350*(0.048)

0.367*(0.046)

0.333*(0.044)

0.450*(0.054)

Age (logged) 0.141*(0.061)

0.324*(0.060)

0.232*(0.057)

0.566*(0.060)

0.300*(0.050)

0.252*(0.056)

0.220*(0.057)

0.232*(0.059)

0.191*(0.071)


0.051*(0.015)

0.067*(0.014)

0.053*(0.016)

0.054*(0.014)

0.054*(0.014)

0.055*(0.014)

0.054*(0.019)

0.008(0.017)

2008 -0.122*(0.041)

0.256*(0.043)

0.003(0.040)

-0.291*(0.042)

0.072(0.040)

0.262*(0.043)

-0.227*(0.043)

-0.041(0.043)

0.000(.)


SI.42

Table SI.4E: The Impact of Informality on Participation in Organizations: Models for Figure 4 (bottom panel)Bolivia Peru Paraguay Chile Uruguay Brazil Venezuela Argentina DR


0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)


-0.059(0.091)

0.022(0.083)

-0.302*(0.097)

0.073(0.113)

0.087(0.089)

0.090(0.122)

0.034(0.079)

-0.187(0.108)

-0.087(0.076)


-0.071(0.077)

0.085(0.065)

-0.091(0.079)

0.052(0.106)

-0.076(0.076)

0.183(0.113)

-0.048(0.070)

0.063(0.100)

-0.074(0.070)


0.132(0.305)

0.931(0.574)


-0.458*(0.077)

-0.196*(0.064)

-0.299*(0.082)

-0.155*(0.076)

-0.263*(0.056)

-0.205(0.105)

-0.238*(0.056)

-0.237*(0.077)

-0.255*(0.063)


0.018*(0.005)

0.027*(0.006)

0.024*(0.009)

0.034*(0.006)

0.025*(0.008)

0.008(0.006)

0.007(0.008)

0.028*(0.005)

Woman 0.286*(0.053)

0.303*(0.043)

0.182*(0.058)

0.661*(0.067)

0.364*(0.048)

0.449*(0.065)

0.343*(0.044)

0.373*(0.066)

0.193*(0.046)

Age (logged) 0.407*(0.072)

0.310*(0.059)

0.529*(0.078)

0.147(0.084)

-0.090(0.059)

0.275*(0.085)

0.471*(0.061)

0.525*(0.081)

0.147*(0.058)


0.084*(0.013)

0.105*(0.017)

0.087*(0.021)

0.052*(0.017)

0.068*(0.022)

-0.008(0.022)

0.080*(0.028)

0.060*(0.013)

2008 0.000(.)

-0.230*(0.040)

0.171*(0.049)

0.000(.)

0.094*(0.046)

0.000(.)

-0.148*(0.043)

0.000(.)

0.062(0.041)


SI.43

Table SI.4F: The Impact of Informality on Participation in Organizations: Ordered Probit Models for Figure 4 (bottom panel)Region


0.000(.)


-0.047(0.031)


0.024(0.027)



-0.252*(0.019)

Education 0.018*(0.002)

Woman 0.324*(0.022)

Age (logged) 0.275*(0.042)


2008 -0.016(0.050)



SI.44

E. Figure 5Table SI.5A: The Impact of Informality on Ideology of Vote Choice: OLS Models for Figure 5 (top panel)

Uruguay El Salv. Brazil Colombia Venezuela NicaraguaFormal Wage Earner

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

Informal -0.184(0.384)

-1.218(0.842)

-0.747*(0.368)

0.036(0.517)

0.014(0.379)

1.988*(0.604)


2.951(3.714)

3.740(2.963)


0.451(0.333)

-1.701*(0.777)

-0.288(0.373)

-0.325(0.451)

0.214(0.348)

1.452*(0.577)


-0.302*(0.064)

0.089*(0.031)

-0.248*(0.047)

0.123*(0.031)

0.029(0.044)

Woman 0.133(0.277)

1.947*(0.559)

-0.109(0.243)

0.912*(0.390)

0.113(0.269)

0.208(0.384)

Age (logged) 2.049*(0.372)

-0.037(0.733)

0.395(0.324)

-0.465(0.527)

0.083(0.393)

0.155(0.484)


-1.143*(0.185)

-0.025(0.084)

-0.207(0.174)

-0.022(0.179)

-0.092(0.116)

Constant 2.016(1.499)

18.114*(2.932)

6.351*(1.329)

18.822*(2.114)

3.033(1.669)

10.276*(2.021)

Observations 908 807 994 802 927 871Standard errors in parentheses* p<0.05

SI.45

Table SI.5B: The Impact of Informality on Ideology of Vote Choice: OLS Models for Figure 5 (top panel)Ecuador Peru Costa Rica Argentina Mexico Guatemala

Formal Wage Earner

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

Informal -0.079(0.314)

-0.249(0.285)

0.504(0.411)

0.137(0.197)

-1.175*(0.488)

-0.112(0.493)


0.585(0.331)

-0.225(0.290)

0.008(0.294)

0.289(0.197)

-0.567(0.489)

0.093(0.534)


1.058(1.636)


0.111*(0.024)

-0.134*(0.028)

0.073*(0.020)

0.004(0.046)

0.070(0.039)

Woman -0.636*(0.221)

1.085*(0.192)

0.371(0.273)

-0.132(0.159)

-0.069(0.396)

-0.503(0.348)

Age (logged) 0.198(0.292)

-0.109(0.253)

-0.553(0.308)

0.385(0.211)

-0.435(0.502)

0.458(0.432)


0.269*(0.057)

-0.127(0.075)

0.146*(0.073)

-0.667*(0.115)

0.434*(0.116)

Constant 5.543*(1.242)

9.374*(1.104)

13.977*(1.220)

6.492*(0.880)

16.955*(2.108)

8.453*(1.702)


SI.46

Table SI.5C: The Impact of Informality on Ideology of Vote Choice: OLS Models for Figure 5 (top panel)Region

DV: Ideology of Vote ChoiceFormal Wage Earner

0.000(.)

Informal -0.027(0.194)



0.124(0.201)

Education -0.022(0.046)

Woman 0.253(0.196)

Age (logged) 0.194(0.260)


2008 -0.317(1.636)

Constant 10.138*(2.265)

lns1_1_1Constant 0.987*

(0.180)lnsig_eConstant 1.506*


SI.47

Table SI.5D: The Impact of Informality on Ideology of Vote Choice: OLS Models for Figure 5 (bottom panel)Uruguay El Salv. Brazil Colombia Venezuela Nicaragua

Formal Wage Earner

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)


-0.319(0.591)

-0.563(1.080)

-0.708(0.433)

1.408(0.804)

0.027(0.490)

1.540*(0.777)


-0.119(0.441)

-1.535(0.903)

-0.775(0.403)

-0.495(0.568)

0.007(0.425)

2.160*(0.632)


2.948(3.714)

3.722(2.955)


0.453(0.333)

-1.712*(0.777)

-0.290(0.374)

-0.346(0.450)

0.214(0.348)

1.458*(0.577)


-0.301*(0.064)

0.088*(0.031)

-0.246*(0.047)

0.123*(0.031)

0.030(0.045)

Woman 0.131(0.278)

1.957*(0.559)

-0.111(0.243)

0.960*(0.390)

0.113(0.270)

0.204(0.384)

Age (logged) 2.036*(0.375)

0.040(0.737)

0.399(0.325)

-0.327(0.529)

0.082(0.394)

0.146(0.484)


1.144*(0.185)

0.026(0.084)

0.205(0.173)

0.022(0.179)

0.094(0.116)

Constant -0.672(1.569)

10.974*(3.226)

6.189*(1.376)

17.055*(2.355)

2.906(1.656)

9.735*(2.109)


SI.48

Table SI.5E: The Impact of Informality on Ideology of Vote Choice: OLS Models for Figure 5 (bottom panel)Ecuador Peru Costa Rica Argentina Mexico Guatemala

Formal Wage Earner

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)


-0.298(0.390)

-0.113(0.394)

-0.241(0.664)

0.141(0.238)

-1.285(0.701)

-0.393(0.569)


0.026(0.333)

-0.289(0.296)

0.860(0.481)

0.132(0.256)

-1.128*(0.532)

0.064(0.525)


1.046(1.635)


0.590(0.331)

-0.226(0.290)

-0.011(0.294)

0.289(0.197)

-0.568(0.490)

0.102(0.534)


0.110*(0.024)

-0.136*(0.028)

0.073*(0.020)

0.005(0.046)

0.072(0.039)

Woman -0.633*(0.221)

1.081*(0.193)

0.411(0.274)

-0.132(0.160)

-0.064(0.397)

-0.498(0.348)

Age (logged) 0.173(0.293)

-0.094(0.255)

-0.619*(0.312)

0.386(0.211)

-0.443(0.503)

0.425(0.434)


-0.268*(0.057)

0.125(0.075)

-0.146*(0.073)

0.666*(0.115)

-0.433*(0.116)

Constant 6.376*(1.304)

10.946*(1.139)

13.474*(1.317)

7.366*(0.859)

12.982*(2.206)

11.149*(1.933)


SI.49

Table SI.5F: The Impact of Informality on Ideology of Vote Choice: OLS Models for Figure 5 (bottom panel)Region

DV: Ideology of Vote ChoiceFormal Wage Earner

0.000(.)


0.046(0.191)


-0.065(0.221)



0.123(0.202)

Education -0.022(0.046)

Woman 0.252(0.194)

Age (logged) 0.200(0.258)


2008 -0.319(1.639)

Constant 9.133*(2.171)




SI.50

F. Figure 6Table SI.6A: The Impact of Informality on Market Policy Attitudes: OLS Models for Figure 6 (top panel)

Mexico Guatemala El Salv. Honduras Nicaragua Costa Rica Panama Colombia EcuadorFormal Wage Earner

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

Informal 0.162*(0.069)

-0.041(0.102)

0.018(0.054)

-0.169(0.093)

0.103(0.082)

-0.054(0.070)

-0.032(0.079)

0.107(0.075)

-0.053(0.064)


0.100(0.069)

-0.141(0.107)

0.030(0.052)

0.099(0.087)

0.036(0.074)

0.045(0.055)

-0.043(0.060)

0.110(0.059)

-0.055(0.066)

Education 0.015*(0.007)

-0.014(0.008)

-0.001(0.004)

0.012(0.007)

0.015*(0.005)

0.005(0.006)

0.009(0.007)

-0.002(0.006)

-0.000(0.006)

Woman 0.000(0.056)

0.058(0.065)

0.023(0.038)

-0.012(0.061)

0.001(0.049)

-0.117*(0.050)

-0.058(0.051)

-0.011(0.048)

0.015(0.047)

Age (logged) 0.049(0.063)

0.155*(0.078)

0.047(0.045)

-0.026(0.068)

0.102(0.057)

0.059(0.062)

0.033(0.060)

-0.108(0.060)

0.007(0.058)


-0.046*(0.021)

-0.012(0.012)

0.078*(0.019)

0.047*(0.015)

0.023(0.015)

-0.081*(0.015)

0.017(0.021)

-0.013(0.015)

Constant -0.603*(0.264)

-0.136(0.306)

-0.374*(0.185)

0.323(0.284)

-0.877*(0.232)

-0.309(0.252)

0.222(0.260)

0.060(0.244)

0.247(0.252)


SI.51

Table SI.6B: The Impact of Informality on Market Policy Attitudes: OLS Models for Figure 6 (top panel)Bolivia Peru Paraguay Chile Uruguay Brazil Venezuela Argentina DR

Formal Wage Earner

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

Informal -0.051(0.050)

0.024(0.067)

-0.159*(0.071)

-0.028(0.057)

-0.072(0.057)

0.031(0.070)

-0.077(0.081)

-0.097(0.051)

-0.061(0.056)


0.041(0.051)

0.040(0.068)

-0.173*(0.080)

-0.012(0.046)

0.009(0.048)

0.077(0.069)

-0.010(0.074)

0.058(0.051)

0.006(0.053)

Education -0.003(0.004)

0.003(0.006)

0.016*(0.006)

0.014*(0.006)

0.043*(0.006)

0.007(0.006)

0.019*(0.007)

0.015*(0.006)

0.000(0.004)

Woman -0.001(0.033)

0.031(0.046)

0.063(0.050)

-0.012(0.041)

-0.047(0.041)

0.013(0.045)

0.047(0.052)

-0.016(0.041)

0.038(0.038)

Age (logged) 0.035(0.041)

0.046(0.058)

0.062(0.066)

-0.043(0.049)

0.156*(0.048)

-0.050(0.056)

-0.063(0.069)

-0.037(0.052)

-0.069(0.049)


-0.001(0.014)

0.026(0.015)

0.048*(0.013)

0.008(0.014)

0.018(0.016)

-0.037(0.023)

0.062*(0.020)

0.011(0.011)

Constant -0.126(0.177)

-0.265(0.251)

-0.769*(0.282)

-0.316(0.218)

-1.201*(0.199)

0.213(0.233)

0.682*(0.292)

-0.458(0.236)

-0.105(0.209)


SI.52

Table SI.6C: The Impact of Informality on Market Policy Attitudes: OLS Models for Figure 6 (top panel)Region

DV: Market Policy AttitudesFormal Wage Earner

0.000(.)

Informal -0.030(0.022)


0.010(0.016)

Education 0.007*(0.003)

Woman 0.003(0.010)

Age (logged) 0.025(0.018)


Constant -0.205(0.111)

lns1_1_1Constant -1.362*

(0.155)lnsig_eConstant -0.200*


SI.53

Table SI.6D: The Impact of Informality on Market Policy Attitudes: OLS Models for Figure 6 (bottom panel)Mexico Guatemala El Salv. Honduras Nicaragua Costa Rica Panama Colombia Ecuador

Formal Wage Earner

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)


0.213*(0.099)

-0.161(0.115)

0.072(0.070)

-0.263*(0.121)

0.223*(0.108)

-0.169(0.091)

-0.050(0.125)

0.091(0.074)

-0.198*(0.079)


0.139(0.076)

0.040(0.109)

-0.011(0.058)

-0.130(0.098)

0.049(0.084)

0.065(0.089)

-0.025(0.088)

0.046(0.057)

0.021(0.068)


0.101(0.069)

-0.138(0.107)

0.028(0.052)

0.100(0.087)

0.037(0.074)

0.045(0.055)

-0.042(0.060)

0.089(0.057)

-0.055(0.066)

Education 0.016*(0.007)

-0.013(0.008)

-0.001(0.004)

0.012(0.007)

0.015*(0.005)

0.005(0.006)

0.009(0.007)

-0.006(0.005)

0.000(0.006)

Woman -0.001(0.056)

0.064(0.065)

0.024(0.038)

-0.011(0.060)

-0.001(0.049)

-0.116*(0.050)

-0.058(0.051)

0.009(0.040)

0.020(0.047)

Age (logged) 0.054(0.063)

0.134(0.079)

0.055(0.046)

-0.029(0.069)

0.111(0.057)

0.046(0.062)

0.033(0.060)

-0.120*(0.051)

-0.010(0.059)


0.045*(0.021)

0.013(0.012)

-0.078*(0.019)

-0.047*(0.015)

-0.022(0.015)

0.081*(0.015)

-0.014(0.018)

0.010(0.015)

Constant -0.227(0.280)

-0.347(0.340)

-0.477*(0.199)

0.800*(0.308)

-0.621*(0.244)

-0.124(0.261)

-0.263(0.272)

0.231(0.222)

0.228(0.261)


SI.54

Table SI.6E: The Impact of Informality on Market Policy Attitudes: OLS Models for Figure 6 (bottom panel)Bolivia Peru Paraguay Chile Uruguay Brazil Venezuela Argentina DR

Formal Wage Earner

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)

0.000(.)


-0.007(0.063)

0.130(0.094)

-0.149(0.084)

-0.035(0.071)

-0.083(0.080)

0.015(0.082)

0.042(0.099)

-0.217*(0.054)

-0.072(0.064)


-0.071(0.052)

-0.025(0.070)

-0.164*(0.073)

-0.020(0.074)

-0.065(0.066)

0.042(0.077)

-0.156(0.092)

0.022(0.069)

-0.052(0.063)


0.042(0.051)

0.037(0.068)

-0.173*(0.080)

-0.012(0.046)

0.009(0.048)

0.078(0.069)

-0.010(0.074)

0.056(0.051)

0.006(0.054)

Education -0.003(0.004)

0.001(0.006)

0.016*(0.006)

0.014*(0.006)

0.044*(0.006)

0.007(0.006)

0.018*(0.007)

0.016*(0.006)

0.001(0.004)

Woman -0.001(0.033)

0.023(0.046)

0.063(0.050)

-0.012(0.041)

-0.047(0.041)

0.014(0.045)

0.043(0.052)

-0.003(0.041)

0.040(0.039)

Age (logged) 0.041(0.042)

0.059(0.058)

0.064(0.067)

-0.044(0.050)

0.155*(0.048)

-0.052(0.056)

-0.059(0.069)

-0.051(0.052)

-0.071(0.050)


0.003(0.014)

-0.026(0.015)

-0.048*(0.014)

-0.008(0.014)

-0.018(0.016)

0.035(0.023)

-0.064*(0.020)

-0.011(0.011)

Constant -0.157(0.191)

-0.298(0.255)

-0.618*(0.287)

-0.026(0.225)

-1.150*(0.208)

0.325(0.247)

0.455(0.310)

-0.047(0.215)

-0.032(0.208)


SI.55

Table SI.6F: The Impact of Informality on Market Policy Attitudes: OLS Models for Figure 6 (bottom panel)Region

DV: Market Policy AttitudesFormal Wage Earner

0.000(.)


-0.042(0.033)


-0.025(0.021)


0.009(0.016)

Education 0.007*(0.003)

Woman 0.004(0.010)

Age (logged) 0.021(0.018)


Constant -0.136(0.108)




SI.56

V. Matching ResultsWe also ran the regionwide hierarchical models using the preprocessing step of coarsened

exact matching,4 trying to maximize balance on the Informal treatment variable. In doing so, these analyses are limited to informal workers (informal self-employed and wage earners) and formal wage earners. All other respondents are dropped.

The only substantive difference of note is a doubling in the size of the informality coefficient in the partisanship model in Table SI.9. However, the substantive effect of informality (lowering the rate of partisanship by 4.5 percentage points, or about 1/10th of a standard deviation) remains modest at best.

Table SI.7: The Impact of Informality on Participation: Coarsened Exact Matching Results (Compare to Table SI.1C)

RegionDV: Political Participation IndexFormal Wage Earner

0.000(.)

Informal -0.001(0.041)

Education 0.040*(0.005)

Woman -0.051(0.039)

Age (logged) 0.475*(0.050)


2008 -0.078(0.053)

Constant -1.878*(0.221)

LnalphaConstant 0.138*



4 Iacus, Stefano, Gary King, Giuseppe Porro (2012). “Causal Inference without Balance

Checking: Coarsened Exact Matching.” Political Analysis 20:1-24.

SI.57

Table SI.8: The Impact of Informality on Turnout: Coarsened Exact Matching Results (Compare to Table SI.2C)

RegionDV: TurnoutFormal Wage Earner

0.000(.)

Informal -0.097*(0.030)

Education 0.047*(0.004)

Woman 0.022(0.028)

Age (logged) 1.252*(0.106)


2008 0.015(0.059)

Constant -3.808*(0.364)



SI.58

Table SI.9: The Impact of Informality on Partisanship: Coarsened Exact Matching Results (Compare to Table SI.3C)

RegionDV: PartisanshipFormal Wage Earner

0.000(.)

Informal -0.130*(0.023)

Education 0.017*(0.007)

Woman -0.119*(0.030)

Age (logged) 0.445*(0.057)


2008 -0.035(0.085)

Constant -1.868*(0.273)



SI.59

Table SI.10: The Impact of Informality on Participation in Organizations: Coarsened Exact Matching Results (Compare to Table SI.4C)

RegionDV: Organizational ParticipationFormal Wage Earner

0.000(.)

Informal 0.029(0.023)

Education 0.021*(0.002)

Woman 0.244*(0.025)

Age (logged) 0.367*(0.040)


2008 0.009(0.050)

cut1Constant 1.205*

(0.175)cut2Constant 1.689*

(0.164)cut3Constant 2.927*



SI.60

Table SI.11: The Impact of Informality on Ideology of Vote Choice: Coarsened Exact Matching Results (Compare to Table SI.5C)

RegionDV: Ideology of Vote ChoiceFormal Wage Earner

0.000(.)

Informal -0.135(0.224)

Education -0.022(0.038)

Woman -0.028(0.217)

Age (logged) -0.130(0.202)


2008 -0.407(1.742)

Constant 11.341*(2.043)




SI.61

Table SI.12: The Impact of Informality on Market Policy Attitudes: Coarsened Exact Matching Results (Compare to Table SI.6C)

RegionDV: Market Policy AttitudesFormal Wage Earner

0.000(.)

Informal -0.006(0.022)


Woman 0.038*(0.014)

Age (logged) 0.038(0.032)


2008 0.000(.)

Constant -0.232(0.147)




SI.62

VI. LAPOP Vote Choice as Nominal Choice ModelsWe reran the model results reported in Figure 5 as nominal choice models. The

ideological scale is an academic construct with highly specific distances among candidates, whereas voters make choices from a discrete choice set knowing, perhaps, the relative ideological positionings of candidates but not their precise placement (if indeed this is knowable at all). To mimic this, we recoded candidates as either left, center, or right using their parties’ placements relative to one another on the Wiesehomeier-Benoit ideological scale.5 We ran one multinomial logit (MNL) per election; we only present models with the larger informal workers category (the top panel in previous figures) since presenting those with the parsed categories would be excessively cluttered. The models treat the leftmost candidate as the omitted base outcome. In most countries, this generates one set of coefficients for the centrist versus leftist binary comparison and another set for the rightist versus leftist comparison.6 In elections with just two major candidates, we designated only one candidate as non-leftist and estimated just one set of coefficients. Figure SI.2 reports the coefficients on informality from these models. Overall, just five of 20 coefficients are statistically distinguishable from zero, and only two of these show informal workers to be more rightward.

Figure SI.2: The Impact of Informality on Vote Choice (Nominal Measure): Evidence from 12 Latin American Elections

5 We limit the analysis to respondents who voted for one of the top three finishers.

6 The choice between two non-leftist candidates of which is centrist and which is rightist is thus

immaterial.

SI.63

VII. Household Wealth as a Covariate

Table SI.13 (Rerun of Table 3 Models): The Impact of Informality on Vote Choice: Argentina 2015 and Brazil 2014 Presidential Elections

Argentina 2015 Brazil 2014OLS MNL OLS MNL

MacriScioli

MassaScioli

NevesRousseff

SilvaRousseff

Informal workers -.472(.360)

-.340(.205)

-.227(.340) Informal workers .093

(.329).012

(.253)-.252(.271)

Formal wage earners

Omitted baseline

Omitted baseline

Omitted baseline Formal workers Omitted

baselineOmitted baseline

Omitted baseline

Formal business owner

.366(.642)

.241(.360)

.235(.577)

Non-EAP -.353(.331)

-.251(.188)

.038(.312) Non-EAP -.082

(.331)-.071(.262)

-.056(.261)

Education .337*(.0105)

.217*(.062)

.020(.108) Education .107

(.055).079

(.045).009

(.050)

Woman -.081(.261)

-.103(.152)

-.321(.252) Woman .137

(.257).098

(.202)-.077(.223)

Age .005(.008)

.002(.005)

.008(.008) Age .011

(.009).007

(.007)-.002(.009)

Urbanicity -.193(.438)

-.034(.280)

-.603(.355) Urbanicity .484

(.340).538

(.304).608

(.404)

Household Wealth .189(.102)

.161*(.060)

.277*(.098) Household Wealth .181*

(.088).177*(.071)

.161*(.077)

Constant 10.364(.795)

-1.155(.474)

-2.024(.756) Constant 5.676

(.842)-3.088(.702)

-2.152(.712)

N 1,147 1,102 N 1,010 985Note: * = p < .05Source: BEPS 2014 and APES 2015.

SI.64

Table SI.14 (Rerun of Table 4 Models): The Impact of Informality on Social Policy Attitudes: Argentina 2015 and Brazil 2014 Presidential Elections

Argentina 2015 Brazil 2014Ordered probit

Support for AUH

MNL OLS MNLPF

ANSESPF

NeitherMeans-

test indexBF

INSSBF

BothInformal workers .048

(.104).220

(.164).292

(.182) Informal workers .202*(.074)

.242(.250)

.266(.237)

Formal wage earners

Omitted baseline

Omitted baseline

Omitted baseline Formal workers Omitted

baselineOmitted baseline

Omitted baseline

Formal business owner

.043(.163)

-.578*(.317)

-.114(.361)

Non-EAP .040(.091)

.223(.155)

.129(.169) Non-EAP .076

(.071).324

(.252).573*(.235)

Education -.035(.028)

-.103*(.051)

-.225*(.055) Education -.082*

(.011)-.007(.040)

-.016(.045)

Woman -.107(.074)

-.011(.120)

-.039(.136) Woman .027

(.054)-.481*(.209)

-.010(.188)

Age -.003(.002)

-.012*(.004)

-.015*(.004) Age -.010*

(.002)-.019*(.007)

-.010(.007)

Urbanicity -.049(.122)

-1.167*(.202)

-.854*(.219) Urbanicity -.227*

(.057)-.566*(.368)

-.176(.267)

Household wealth -.046(.028)

-.184*(.044)

-.316*(.051)

Household Wealth

-.132*(.019)

-.275*(.068)

-.066(.073)

Constant NA 2.003(.371)

3.075(.406) Constant 1.188

(.160)3.814(.669)

1.241(.664)

N 1,119 2,336 N 3,058 1,071Note: * = p < .05Source: BEPS 2014 and APES 2015.

SI.65

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