LSMS datasets are invaluable for poverty research but each country uses different variable names, food codes, and file formats. Rather than harmonizing the data itself, LSMS_Library provides an abstraction layer that standardizes how you access the data, preserving granularity that traditional harmonization loses.

Overview

LSMS_Library is a Python library offering uniform access to Living Standards Measurement Study (LSMS) household surveys across multiple countries and years. Each country uses different variable names, food classifications, questionnaire structures, and file formats. Researchers either invest weeks learning each dataset or settle for pre-harmonized data that sacrifices detail.

Rather than harmonizing data itself, the library provides an abstraction layer that standardizes how you access the data across different LSMS surveys. Install via pip install LSMS_Library and access data through consistent method calls returning standardized DataFrames.

Citation

@Software{	  ligon25lsms,
  author	= {Ethan Ligon},
  title		= {{LSMS\_Library}: Abstraction Layer for Living Standards
                Measurement Surveys},
  year		= 2025,
  publisher	= {Zenodo},
  doi		= {10.5281/zenodo.17258079},
  url		= {https://github.com/ligon/LSMS_Library}
}