Cleaning the Relação Anual de Informações Sociais (RAIS) dataset in Stata, 1985-2018

This repository contains Stata code that cleans and normalizes all RAIS for years 1985-2018.

More information about RAIS, the Brazilian matched employer-employee dataset:

• Base dos Dados
• Ministério da Economia

Requirements

• Stata (preferably version 14+)

Basic Usage

1. Clone or download the repository.
2. Paste the raw RAIS data files into /input.
3. Run each year's dofile in /src/sub. Adjust the directory path to your own setup.
4. Run the dofile /src/sub/build_subsets.do.
5. Run the dofile /src/sub/build_collapses.do.

Output

This repository outputs RAIS all cleaned and normalized. It generates three sets of main datasets: (1) at worker-establishment-municipality level, (2) at worker-municipality level, (3) at establishment-municipality level. It also builds collapsed data sets at establishment-municipality and establishment level.

It provides some cleaning fixes to the original data:

• It standardizes all variable names and labels.
• It fixes wage variables with missing values.
• It generates deflated wage variables, relative to 2018.
• It allows for sample output data sets, if one prefers to work with smaller files.
• It standardizes classification variables (CNAE and CBO), and builds IBGE's broad sectors variables.
• It classifies types of establishments, into public, private, nonprofit, and by sphere/branch of government.
• It reconstructs CPF data back to years before 2003, for workers who show up in prior years.

Tips

• See the file /extra/Variables_RAIS_1985-2018.xlsx for a complete dictionary of variables, labels, values and availability year-by-year.
• Identified RAIS data is not public. To get access to it, one must (1) be in an university/institution that already has an agreement with the Ministério da Economia, or (2) apply for new access.
• Run this in a server with supercomputer capabilities. RAIS files are large.
• For advice on structuring directories and code, please refer to my template repository.
• Prof. Marc Muendler (UCSD) has useful material about RAIS.

Credits

If you benefit from code in this repository, please cite it in your work as:

• Dahis, Ricardo (2020) Cleaning the Relação Anual de Informações Sociais (RAIS) dataset, 1985-2018. Github repository - https://github.com/rdahis/clean_RAIS

Bugs, Comments and Suggestions

If you find any issues in my code, or have any suggestions for improvements, please open an issue or just email me at [email protected].