Evaluating the impact of two low-cost interventions to reduce discrimination against Venezuelan migrant students in Ecuador

Last registered on September 19, 2022


Trial Information

General Information

Evaluating the impact of two low-cost interventions to reduce discrimination against Venezuelan migrant students in Ecuador
Initial registration date
September 13, 2022

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
September 19, 2022, 4:08 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.



Primary Investigator


Other Primary Investigator(s)

PI Affiliation
PI Affiliation
PI Affiliation

Additional Trial Information

On going
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
This study aims to provide new causal evidence on the prejudices faced by immigrant students and solutions to mitigate them. Segregation and discriminatory attitudes represent a major barrier to immigrant children integration. While teachers’ negative stereotypes can have permanent adverse consequences on children’s human capital accumulation, relatively little is known about how to reduce and prevent such biases. We focus on Ecuador, a country that has received unprecedented large inflows of Venezuelan immigrants over the past five years. Using administrative data of end-of-term exam grades as well as objective performance measures from standardized test scores, we evaluate the impact of two interventions directed to school teachers: first, a short video that reveals information on equal performance and ambitions of natives and immigrant students, second, we provide personalized feedback on own implicit biases using an Implicit Association Test. The study will constitute one of the first interventions in the region to reduce bias against immigrant students.
External Link(s)

Registration Citation

Drouet, Marcelo et al. 2022. "Evaluating the impact of two low-cost interventions to reduce discrimination against Venezuelan migrant students in Ecuador." AEA RCT Registry. September 19. https://doi.org/10.1257/rct.10066-1.0
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Experimental Details


We evaluate the impact of two low-cost interventions:

1. An informative video: We present a video to around half of the teachers randomly selected at the school level. Considering that perspective-taking and experiencing the emotions of a minority group might be an effective debiasing strategy (Bertrand and Duflo, 2017), the video starts by providing background information about the Venezuelan exodus focusing on the children involved and the challenges they face upon arrival. Then, we provide evidence showing that the performance of immigrant students is comparable to the one of Ecuadorians and that the future aspirations of both groups are equally high.
We measure the effect of this low-cost intervention on the end-of-term exams of the first semester.

2. IAT feedback. We invite all teachers to take an immigration IAT adjusted to measure stereotypes between Venezuelans and Ecuadorians. We randomly select a group of teachers to receive feedback on their implicit bias towards immigrant students according to their IAT score just after they complete the test. We evaluate the effect of the second intervention on the end-of term exams of the second semester. After teacher grade the second semester, we will give feedback about the IAT score to the control group.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
End of term grades at student level
Migrant IAT at teacher level
Explicit bias against migrants at the teacher level
Primary Outcomes (explanation)
The main objective of this study is to provide causal evidence on discrimination experienced by immigrant students and to evaluate the impact of two low-cost interventions that aim to reduce teachers’ bias in grading against this group. The first one is based on an informative video while the second one provides IAT feedback. We focus on Ecuador, a country that has received sudden and increasing inflows of Venezuelan immigrants over the past five years.

First, we measure whether there exists a de-facto bias against immigrant students by exploiting administrative records that allow us to compare native and immigrant students’ grades based on exams graded by their teachers, controlling by their performance on anonymous standardized national exams (Ser Estudiante, Ser Bachiller). Complementarily we design and administer a survey in order to construct a measure of teachers’ explicit bias towards immigrant students through self-reported attitudes. The survey is administered online before the interventions. It allows us to construct a psychometric measurement instrument based on standard questions from the Gallup's Migrant Acceptance Index and the World Values Survey. The survey collects information on teachers’ beliefs about the performance and aspirations of migrants compared to natives as well as from other minority or vulnerable groups. We expect that not focusing exclusively on migrants will prevent teachers from reinforcing their attitudes towards them before they receive treatment. Additionally, we gather teachers’ demographic and socioeconomic information that we use in our estimations as controls.

After the survey, we proceed with the first intervention. We present a 2-minute informative video to the teachers who were randomly allocated to treatment. Notice that randomization takes place at the school level rather than at the teacher level to avoid contamination between teachers. The treatment takes place before the semester ends which allows us to estimate its impact on the end-of-term grades of the first semester (end of September) by comparing treatment and control groups. We are also able to explore treatment effect heterogeneity by exploiting the information on beliefs gathered previously in the survey.

The second part of this study takes place at the beginning of the second semester and follows closely the study of Alesina et. al. 2018. We develop an Implicit Association Test (IAT) that allows us to measure teachers’ implicit bias. This computer-based test reduces the influence of social desirability bias in self-reported replies (Greenwald et al., 2009, Alesina et. al. 2018) by measuring the difference in reaction times when teachers are asked to associate positive and negative attributes with Venezuelan (immigrant) and Ecuadorian (native) representations. We then explore to what extent the difference in grading is associated with implicit stereotypes and compare how they relate to the explicit bias identified in the survey.

Finally, the second intervention consists of providing feedback via e-mail on the IAT results to a randomized group of teachers. Using the second-semester grades as an outcome, we will evaluate whether generating awareness of each one’s stereotypes can reduce discriminatory behavior. We randomize at the school-level again among the teachers that received the first treatment and the teachers that were in the first control group, which would allow us to i) measure the impact of both interventions combined and ii) to determine which one is more effective at reducing teachers’ bias in grading against immigrant students.

The final outcome to evaluate would be the grades at the end of the academic year (February 2023), in which we will able to evaluate both interventions.

Alan, S., Duysak, E., Kubilay, E. & Mumcu, I., 2021. Social Exclusion and Ethnic Segregation in Schools: The Role of Teacher’s Ethnic Prejudice.
Alesina, A., Carlana, M., La Ferrara, E. & Pinotti, P., 2018. Revealing Stereotypes: Evidence from Immigrants in Schools. NBER Working Paper Series, Issue 25333.
Bertrand, M., & Duflo, E. (2017). Field experiments on discrimination. Handbook of economic field experiments, 1, 309-393.
Carlana, M., 2019. Implicit Stereotypes: Evidence from teachers´gender bias. The Quarterly Journal of Economics.
Castro, J. y otros, 2010. Desigualdad de Oportunidades educativas y segmentación laboral en la población de 15 a 29 años de Brasil y Colombia según autoclasificación racial, 2010: Universidad del Valle.
Gertler, P. y otros, 2016. Impact Evaluation in Practice. Washington D.C: World Bank Group and Inter-American Development Bank.
Khandker, S. R., Koowal, G. B. & Samad, H. A., 2010. Randomization. En: Handbook on Impact Evaluation. Quantitative Methods and Practices. Washington D.C.: The World Bank, pp. 33-52.
Greenwald, A. G., Nosek, B. A., and Banaji, M. R. (2003). Understanding and using the Implicit Association Test: I. An improved scoring algorithm. Journal of personality and social psychology, 85(2):197.
Nosek, B. A., Greenwald, A. G. & Banaji, M. R., 2007. The Implicit Association Test at age 7: A methodological and conceptual review. En: Automatic processes in social thinking and behavior. s.l.:Psychology Press, pp. 265-292.
Peña, Y., 2016. Evaluación del prejuicio racial implícito (IAT): Caso República Dominicana. Ciencia y Sociedad, pp. 77-111.
Rodríguez, C., Cárdenas, J. C., Oviedo, J. D. & Villamizar, S., 2013. La discriminación racial en el trabajo. Un estudio experimental en Bogotá, Bogotá: Centros de Estudios de Derecho, Justicia y Sociedad, Dejusticia.
Webber, S. & Prouse, C., 2018. The New Gold Standard: The Rise of Randomized Control Trials and Experimental Development. Economic Geography, pp. 166-187.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
In this study we will replicate the work of Alesina et.al (2018), in Italian schools, adapted for the context of Ecuador. This design seeks to answer the following questions:

1. Are teachers in Ecuador biased against immigrant Venezuelan students?
2. Can a low-cost general informative intervention help reduce the bias against immigrant students?
3. Do teachers change their behavior when they are aware of their own implicit stereotypes?

We select teachers from 700 public schools that have at least 3 Venezuelan students in their class. We then proceed in two stages:

In the first stage we randomly divide schools in two groups: treatment and control. Before the interventions start, all teachers and school directors receive an invitation to participate in a study that aims to strengthen the relationship between teachers and students. We announce that participants will have to complete two surveys. In this invitation, we do not mention anything related to immigration, discrimination or teachers’ bias. The week before the first semester exams, those participating in the study will receive via e-mail the following:

● Treatment 1: A survey that collects sociodemographic characteristics and teachers’ beliefs followed by the informative video (intervention 1).
● Control 1: The same survey as the treatment group but no video.

We will then measure the impact of the video intervention on the grades differences of the first semester exams.

The second stage focuses on the IAT treatment (intervention 2). We split randomly the treatment and control groups defined before into two groups each, ending with four arms (conditional on the number of schools that participate in the first part of the study).. After the first semester but before the second semester exams, all participants will receive a second survey with the IAT instrument.
● Treatment 1 is divided in two groups:
○ Treatment 1 (Video) + Treatment 2 (IAT feedback): Receive a survey with an IAT followed by feedback on their IAT score
○ Treatment 1 (Video) - Control 2 (No IAT feedback): Receive a survey with an IAT but no feedback is provided before the study ends.
● Control 1 is divided in two groups:
○ Control 1 (No video) + Treatment 2 (IAT feedback): Receive a survey with an IAT followed by feedback on their IAT score.
○ Control 1 (No video) + Control 2 (No IAT feedback): Receive a survey with an IAT but no feedback is provided before the study ends.

We will then measure the impact of the IAT intervention on the grades differences of the second semester exams.

At each stage, the randomization is performed at the school level rather than at the teacher level to avoid contamination between those that received the video and those who did not. Furthermore, it prevents unrest for those teachers that do not receive the IAT feedback.
Experimental Design Details
We will randomly divide 700 schools where there is at least one grade with three venezuelan students. We expect about 13,000 teachers in courses with venezuelan students in total.

We stratified the 700 school regarding area (urban/rural), size (students), courses with venezuelan students, teachers with venezuelan students, amount of venezuelan students.
Randomization Method
Office by a computer
Randomization Unit
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
Sample size: planned number of observations
We expect to survey at least 1600 teachers in 700 schools.
Sample size (or number of clusters) by treatment arms
350 schools control, 350 schools treatment.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
For each state independently (350 schools per arm), the MDE is 0.157 standard deviations. To evaluate the interaction between both interventions (125 schools per arm), the MDE is 0.225 standard deviations.

Institutional Review Boards (IRBs)

IRB Name
Econometria S.A.
IRB Approval Date
IRB Approval Number


Post Trial Information

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