• http://dx.doi.org/10.18235/0004850

Cruces, Guillermo, et al. (2023). Survey Data associated with: A Better World for Migrants in Latin America and the Caribbean. IDB Open Data. https://doi.org/10.60966/fnm3-ab90

1. Spanish

What is this dataset?

A multicountry experimental dataset measuring attitudes towards immigrants and perceptions of migration in Latin America. It contains harmonized microdata from survey experiments conducted across multiple countries (for example, Peru, Colombia, Chile, Mexico, Ecuador, Barbados, and the Dominican Republic), along with country files such as raw-peru.csv, raw-colombia.csv, and a unified dictionary (diccionario.xlsx).

What was the experimental design?

Participants were randomly assigned to one of three groups: - Control (control) - Informational video (informativo) correcting misconceptions about migration scale/characteristics - Emotive video (emotivo) designed to elicit empathy toward migrants
Outcomes include belief updates and stated attitudes towards immigrants, assessed using a battery of questions (e.g., q10–q25, with country-specific ranges).

What questions can I answer with this dataset?

• Do informational vs emotive messages change attitudes towards immigrants?
• Which groups (by age, gender, education) are most responsive?
• How do responses vary across countries and within countries (regions/cities)?
• Which misconceptions (size, characteristics, economic impact) are most amenable to correction?

How do I combine countries for regional migration analysis in Latin America?

1. Inspect dictionaries to align variable names and scales.
2. Append country files, adding a pais identifier if not present.
3. Harmonize response options (e.g., map Likert codes to a shared scale).
4. Cluster standard errors by country (and region where relevant).
5. Include treatment dummies (informativo, emotivo) and interactions with demographics for heterogeneity.

What are standard outcome measures?

• Indices of attitudes towards immigrants (e.g., warmth, acceptance of rights, support for inclusion policies).
• Knowledge/belief scores about migration size and characteristics (pre/post or post-only depending on the arm).
• Policy support items related to migrant integration or restrictions.

How should I estimate treatment effects?

• Intention-to-Treat: regress outcomes on informativo and emotivo (control is the omitted group), with country (and optionally region) fixed effects.
• Heterogeneity: interact treatment indicators with educacion, edad, genero.
• Multiple-testing controls: if building indices from many items, predefine index construction or adjust p-values.

Are there limitations to the dataset?

• Cultural/linguistic differences: wording may vary across countries; verify item equivalence in the Diccionario.
• Outcome scaling: Likert distributions can be skewed; consider ordered models or standardized indices.
• Short-run effects: outcomes capture immediate/short-term shifts; long-term persistence isn’t directly observed.

What are common attitudes toward immigrants reported in public opinion research?

The dataset measures public perceptions of immigrants using survey responses about social attitudes, trust, and policy preferences. Results show that opinions vary widely across countries and demographic groups, with some respondents expressing concern about economic competition and others supporting inclusive policies.

How do people typically perceive immigrants' economic impact and job competition?

Survey variables indicate that respondents often associate immigration with labor-market competition, especially among lower-income and less-educated groups. However, other respondents report neutral or positive views, suggesting that perceptions depend strongly on socioeconomic context.

How do attitudes toward immigrants vary by age, education, gender, and political ideology?

The dataset allows disaggregation by demographic characteristics, showing that education level and political preferences are strong predictors of attitudes. Higher-educated respondents tend to show more favorable views, while ideological orientation influences support for restrictive or inclusive policies.

Why do some groups hold negative attitudes toward immigrants?

Responses in the dataset link negative perceptions to concerns about security, economic inequality, and institutional trust. Individuals who report low confidence in government or great concern about crime are more likely to express unfavorable views toward immigrants.

What survey questions, scales, and experimental measures are used to measure attitudes toward immigrants?

The dataset includes standardized survey questions measuring perceptions of security, trust, social tolerance, and policy preferences. These variables allow comparison across countries and population groups using consistent coding and methodology.

How do attitudes toward immigrants differ between urban and rural populations?

The dataset includes geographic identifiers that allow comparison across locations. Results show that attitudes vary across regions, with urban respondents often reporting different levels of perceived risk, trust, and policy support than those in less-populated areas.