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Abstract
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Before
This study uses a survey experiment to measure how students and workers in Brazil perceive and value public employment relative to private employment. Participants report baseline beliefs about wages, job stability, and probabilities of entering public and private employment under different search strategies. They are then randomly assigned to receive aggregate labor-market information about one of these topics or to a no-information control condition. After the information module, the survey elicits expected wages, reservation wages, cross-sector switching thresholds, career-path probabilities, willingness to pay for additional information through a Becker-DeGroot-Marschak (BDM) mechanism, and choices over hypothetical jobs in a discrete choice experiment (DCE).
The main hypotheses are that public employment is valued because of a combination of perceived wages, perceived stability, perceived entry probabilities, and non-wage amenities; that information changes beliefs and downstream choices; that demand for information depends on what participants already know and what information they have already received; and that the DCE can recover willingness to pay for public-sector employment, lower dismissal risk, remote work, teamwork, regular hours, and contract type. The analysis will estimate intention-to-treat effects of information on beliefs, reservation wages, crossing thresholds, BDM willingness to pay, and DCE choices, with pre-specified heterogeneity by family public-sector exposure, state, academic program or field, previous experience with concursos publicos, and selected exploratory moderators such as risk tolerance, family norms, mobility constraints, and salary-privacy norms.
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After
This study uses a survey experiment to measure how students and workers in Brazil perceive and value public employment relative to private employment. Participants report baseline beliefs about wages, job stability, and probabilities of entering public and private employment under different search strategies. They are then randomly assigned to receive aggregate labor-market information about one of these topics or to a no-information control condition. After the information module, the survey elicits expected wages, reservation wages, cross-sector switching thresholds, career-path probabilities, willingness to pay for additional information through a Becker-DeGroot-Marschak (BDM) mechanism, and choices over hypothetical jobs in a discrete choice experiment (DCE).
The main hypotheses are that public employment is valued because of a combination of perceived wages, perceived stability, perceived entry probabilities, and non-wage amenities; that information changes beliefs, downstream choices, and behavioral measures of demand for career-related information and tools; that demand for information depends on what participants already know and what information they have already received; and that the DCE can recover willingness to pay for public-sector employment, lower dismissal risk, remote work, teamwork, regular hours, and contract type. The analysis will estimate intention-to-treat effects of information on beliefs, reservation wages, crossing thresholds, BDM willingness to pay, and DCE choices, with pre-specified heterogeneity by family public-sector exposure, state, academic program or field, previous experience with concursos publicos, and selected exploratory moderators such as risk tolerance, family norms, mobility constraints, and salary-privacy norms.
The survey also includes two behavioral measures of downstream demand: whether participants click a link to sign up to receive forthcoming material related to public-sector exams, and whether they choose to enter a lottery for a three-month subscription to either QConcursos, a platform for public-sector exam preparation, or LinkedIn Premium Career, a private-sector-oriented professional platform.
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Last Published
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July 23, 2026 08:11 AM
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After
August 27, 2026 02:00 PM
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Intervention (Public)
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Before
The intervention is a randomized information-provision experiment embedded in an online survey about public and private employment in Brazil. After reporting baseline beliefs about public- and private-sector wages, job stability, and entry probabilities, participants are randomly assigned to receive one short module of objective, aggregate labor-market information on one of three topics — wages, job stability, or probability of entry — or to a no-information control arm. The information is presented as group-level statistics (drawn from Brazil's PNAD Continua for comparable groups) and states explicitly that the figures describe groups and do not determine what will happen to any individual. After the information module, participants complete an incentivized Becker-DeGroot-Marschak (BDM) exercise eliciting willingness to pay for one additional information topic (which is drawn randomly among one of the three topics not yet displayed), and a discrete choice experiment (DCE) in which they choose between pairs of hypothetical jobs that vary in wage, sector, dismissal risk, remote work, teamwork, work pace, and contract type.
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After
The intervention is a randomized information-provision experiment embedded in an online survey about public and private employment in Brazil. After reporting baseline beliefs about public- and private-sector wages, job stability, and entry probabilities, participants are randomly assigned to receive one short module of objective, aggregate labor-market information on one of three topics — wages, job stability, or probability of entry — or to a no-information control arm. The information is presented as group-level statistics (drawn from Brazil's PNAD Continua for comparable groups) and states explicitly that the figures describe groups and do not determine what will happen to any individual. After the information module, participants complete an incentivized Becker-DeGroot-Marschak (BDM) exercise eliciting willingness to pay for one additional information topic (which is drawn randomly among one of the three topics not yet displayed), and a discrete choice experiment (DCE) in which they choose between pairs of hypothetical jobs that vary in wage, sector, dismissal risk, remote work, teamwork, work pace, and contract type.
At the end of the survey, participants are also offered two optional behavioral choices: they may click a link to sign up to receive forthcoming material related to public-sector exams prepared by ENAP (Escola Nacional de Administração Pública), and they may choose whether to enter a lottery for a three-month subscription to either QConcursos or LinkedIn Premium Career. These are outcomes used to measure downstream demand for public-sector-related information and for career-search tools -- not additional randomizations.
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Intervention End Date
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August 31, 2026
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September 30, 2026
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Primary Outcomes (End Points)
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Before
Primary outcomes fall into three families, all measured within the same survey after the R1 information module:
1) Beliefs and belief updating: own expected prospects about wages, one-year job-loss probability, and entry probability under different search strategies.
2) Reservation wages, crossing thresholds, and subjective probabilities: reservation wage in the public sector (RW_P), reservation wage in the private sector (RW_R), the gap RW_R − RW_P and its log version, the minimum public salary required to leave private jobs anchored at R$15,000 and R$20,000, and
the subjective probabilities of future career paths (from zero to 100), in particular: private sector jobs, public sector jobs, entrepreneurship, pursuing further education, moving to a different city, and moving abroad).
3) Willingness to pay for information (BDM): the bid (maximum amount given up) for additional wage, stability, or entry-probability information.
3) DCE choices and implied willingness to pay: the chosen job profile in each of six tasks, and implied monthly willingness to pay for public/statutory employment, lower dismissal risk, remote work, teamwork, respecting regular hours, and contract type (CLT vs PJ, and the public/statutory bundle).
Treatment effects are estimated as intention-to-treat effects of information assignment relative to control, and as topic-specific effects on the corresponding belief family (assigned a topic vs not).
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After
Primary outcomes fall into four families, all measured within the same survey after the R1 information module:
1) Beliefs and belief updating: own expected prospects about wages, one-year job-loss probability, and entry probability under different search strategies.
2) Reservation wages, crossing thresholds, and subjective probabilities: reservation wage in the public sector (RW_P), reservation wage in the private sector (RW_R), the gap RW_R − RW_P and its log version, the minimum public salary required to leave private jobs anchored at R$15,000 and R$20,000, and the subjective probabilities of future career paths (from zero to 100), in particular: private sector jobs, public sector jobs, entrepreneurship, pursuing further education, moving to a different city, and moving abroad).
3) Willingness to pay for information (BDM): the bid (maximum amount given up) for additional wage, stability, or entry-probability information.
4) DCE choices and implied willingness to pay: the chosen job profile in each of six tasks, and implied monthly willingness to pay for public/statutory employment, lower dismissal risk, remote work, teamwork, respecting regular hours, and contract type (CLT vs PJ, and the public/statutory bundle).
Treatment effects are estimated as intention-to-treat effects of information assignment relative to control, and as topic-specific effects on the corresponding belief family (assigned a topic vs not).
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Experimental Design (Public)
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Before
This is an individual-level online survey experiment. The main randomization (R1) assigns each participant to one of four arms: wage information, stability information, entry-probability information, or a no-information control. A second randomization (R2) determines which not-yet-shown information topic is offered in an incentivized BDM exercise and the random price that determines whether it is delivered. A third randomization (R3) generates six pairs of hypothetical job profiles per participant, randomizing job attributes subject to logical restrictions that ensure the job profiles are credible. The main analysis estimates intention-to-treat effects of R1 assignment (relative to control) on beliefs, reservation wages and crossing thresholds, BDM willingness to pay, and DCE choices, with pre-specified heterogeneity by parental public-sector employment, state, program/field, prior concurso experience, and baseline beliefs. Treatment is not clustered; respondent-level standard errors are heteroskedasticity-robust and DCE standard errors are clustered by respondent. The study is fielded to two samples — UnB undergraduates and an online sample of Brazilian workers/job-seekers — analyzed separately and, secondarily, pooled with sample fixed effects and treatment-by-sample interactions.
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After
This is an individual-level online survey experiment. The main randomization (R1) assigns each participant to one of four arms: wage information, stability information, entry-probability information, or a no-information control. A second randomization (R2) determines which not-yet-shown information topic is offered in an incentivized BDM exercise and the random price that determines whether it is delivered. A third randomization (R3) generates six pairs of hypothetical job profiles per participant, randomizing job attributes subject to logical restrictions that ensure the job profiles are credible. The main analysis estimates intention-to-treat effects of R1 assignment (relative to control) on beliefs, reservation wages and crossing thresholds, BDM willingness to pay, DCE choices, and the pre-specified behavioral outcomes measured at the end of the survey, with pre-specified heterogeneity by parental public-sector employment, state, program/field, prior concurso experience, and baseline beliefs. Risk aversion will also be considered as a heterogeneity variable. Treatment is not clustered. Respondent-level standard errors are robust to heteroskedasticity and DCE standard errors are clustered by respondent. The study is fielded to two samples — UnB undergraduates and an online sample of Brazilian workers/job-seekers — analyzed separately and, secondarily, pooled with sample fixed effects and treatment-by-sample interactions.
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Planned Number of Observations
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Up to approx. 2,000 individuals: <=500 undergraduates at the University of Brasilia and <=500 online Brazilian workers/job-seekers. Randomization and the primary respondent-level analyses are at the individual level. For the profile-level DCE analysis only, each respondent contributes 6 tasks x 2 profiles = 12 job-profile records (up to ~12,000 profile observations), but the unit of randomization and of the main outcomes is the individual.
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After
Up to approx. 1,000 individuals: <=500 undergraduates at the University of Brasilia and <=500 online Brazilian workers/job-seekers. Randomization and the primary respondent-level analyses are at the individual level. For the profile-level DCE analysis only, each respondent contributes 6 tasks x 2 profiles = 12 job-profile records (up to ~12,000 profile observations), but the unit of randomization and of the main outcomes is the individual.
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Intervention (Hidden)
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Before
The study contains three nested randomizations delivered within a single Qualtrics survey.
Main information arm (R1). After baseline beliefs, each participant is assigned to one of four conditions with equal probability using an embedded random integer 0–3 (information_group): (a) wage information — public and private gross monthly wage distributions, including medians and 90th percentiles, for workers with higher education and for young workers with higher education; (b) stability information — the number out of 100 public and private workers who are unemployed one year later; (c) entry-probability information — the number out of 100 job seekers who enter public/statutory versus private employment after 12 months under different search strategies, including studying for concursos publicos versus focusing on private-sector vacancies; and (d) control — no labor-market information before the immediate outcome module.
BDM exercise (R2). Participants are told they will receive up to R$5.00 as reimbursement and may give up part of it to obtain one additional information topic (randomized among topics not yet shown). They state the maximum they would give up. The bid menu runs R$0.00–R$5.00 in R$0.50 increments; the random price is drawn as a random integer 0–10 times R$0.50. If the bid is at least the random price, the participant receives the information and pays the random price (not the bid); otherwise they receive nothing and pay nothing. A comprehension question precedes implementation. Participants never spend their own money — any deduction only reduces the participation reimbursement.
Discrete choice experiment (R3). Participants complete six binary choice tasks between two hypothetical jobs, with the instruction that unmentioned characteristics are identical across jobs. Attribute order is randomized once per respondent. For each profile the employer sector is drawn first; public profiles are assigned low dismissal risk and a statutory contract, private profiles low or medium dismissal risk and either CLT or PJ contracts. Wages are an independent multiplier drawn from a uniform [0.5, 1.5) distribution times a reference wage of R$4,784.50 (corresponding to the median salary of workers between ages 22 and 24). In the current instrument statutory contract and public sector are bundled, so the public-sector coefficient should be read as a public/statutory bundle.
Measurement randomizations. Before treatment, the three baseline-belief blocks (stability, wages, entry) are shown in randomized order, and within blocks the order of comparable public/private items is randomized where implemented. These reduce order effects and are not the treatment of interest.
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After
The study contains three nested randomizations delivered within a single Qualtrics survey.
Main information arm (R1). After baseline beliefs, each participant is assigned to one of four conditions with equal probability using an embedded random integer 0–3 (information_group): (a) wage information — public and private gross monthly wage distributions, including medians and 90th percentiles, for workers with higher education and for young workers with higher education; (b) stability information — the number out of 100 public and private workers who are unemployed one year later; (c) entry-probability information — the number out of 100 job seekers who enter public/statutory versus private employment after 12 months under different search strategies, including studying for concursos publicos versus focusing on private-sector vacancies; and (d) control — no labor-market information before the immediate outcome module.
BDM exercise (R2). Participants are told they will receive up to R$5.00 as reimbursement and may give up part of it to obtain one additional information topic (randomized among topics not yet shown). They state the maximum they would give up. The bid menu runs R$0.00–R$5.00 in R$0.50 increments; the random price is drawn as a random integer 0–10 times R$0.50. If the bid is at least the random price, the participant receives the information and pays the random price (not the bid); otherwise they receive nothing and pay nothing. A comprehension question precedes implementation. Participants never spend their own money — any deduction only reduces the participation reimbursement.
Discrete choice experiment (R3). Participants complete six binary choice tasks between two hypothetical jobs, with the instruction that unmentioned characteristics are identical across jobs. Attribute order is randomized once per respondent. For each profile the employer sector is drawn first; public profiles are assigned low dismissal risk and a statutory contract, private profiles low or medium dismissal risk and either CLT or PJ contracts. Wages are an independent multiplier drawn from a uniform [0.5, 1.5) distribution times a reference wage of R$4,784.50 (corresponding to the median salary of workers between ages 22 and 24). In the current instrument statutory contract and public sector are bundled, so the public-sector coefficient should be read as a public/statutory bundle.
Measurement randomizations. Before treatment, the three baseline-belief blocks (stability, wages, entry) are shown in randomized order, and within blocks the order of comparable public/private items is randomized where implemented. These reduce order effects and are not the treatment of interest.
Behavioral outcomes. At the end of the survey, participants are offered two optional behavioral choices. First, participants may click a link to sign up to receive forthcoming public material from Brazil’s Escola Nacional de Administração Pública (ENAP) based on data of public-sector exams. The click itself is recorded as an outcome. Second, participants may choose to enter a lottery for one of two three-month subscriptions: QConcursos (public-sector exam preparation) or LinkedIn Premium Career (professional/job-search platform), or decline to participate. The lottery-entry decision and, conditional on entry, the selected subscription are recorded as outcomes. These behavioral measures allow me to test whether R1 information assignment affects demand for public-sector-related information and the relative demand for tools associated with public-sector exam preparation versus the broader labor market.
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Secondary Outcomes (End Points)
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Before
1) Current employment and job search: employment/internship status, sector and public/private branch, contract type, earnings category, hours, tenure, whether searching for another job, and search method.
2) Information environment: what participants search before applying, and sources used (concurso websites, social networks, family, professors/mentors, job platforms).
3) Concurso experience: whether they studied for a public-sector exam or selection process in the last year and weekly preparation hours.
4) Stated future trajectories and open text: imagined private job, imagined public/statutory job, and ideal-job descriptions; perceived clarity, usefulness, surprise, and specificity of the information shown.
4) Values, mobility, and norms: family-vs-work tradeoffs, perceived control over life, family obligation and neolocality items, willingness to move, salary-privacy norms, and willingness to discuss wages.
5) Risk: general willingness to take risks (0–10) and a simple risky-lottery choice.
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After
1) Behavioral demand outcomes: (i) whether the participant clicks the optional link to sign up to receive forthcoming ENAP material related to public-sector exams; (ii) whether the participant chooses to participate in the subscription lottery; (iii) whether the participant chooses QConcursos; and (iv) whether the participant chooses LinkedIn Premium Career. The latter two outcomes are defined on the full randomized sample, conding as zero participants that chose not to participate in the lottery.
2) Open-text career descriptions and information evaluations: imagined private job, imagined public/statutory job, and ideal-job descriptions; perceived clarity, usefulness, surprise, and specificity of the information shown.
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