EPAR conducts data analyses when we have access to publicly-available datasets with information relevant to our research questions. This page includes links to data sources EPAR has frequently used, a series of data analysis tips and considerations drawing from our experience with data analysis projects, and links to resources for research and statistical analysis.

Browse EPAR Data Analyses on our research page, including our recent and ongoing work on curating a series of Agricultural Development indicators using data from the World Bank's Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA) from Ethiopia, Nigeria, and Tanzania. View publicly available code repositories from past EPAR projects on EPAR’s GitHub page.

Common EPAR Data Sources:

  • Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA): The LSMS-ISA is a comprehensive household survey supported by the World Bank and administered in eight countries in Africa (Burkina Faso, Ethiopia, Malawi, Mali, Niger, Nigeria, Tanzania, and Uganda) in partnership with national government statistical offices. The LSMS-ISA datasets are nationally-representative panel surveys, and include a rich set of agricultural data as well as a household module with a variety of questions of socio-economic status, household welfare, and non-farm income activities.
  • Food and Agriculture Organization of the United Nations (FAO): The FAO hosts FAOSTAT, a data platform housing global agricultural statistics.
  • Agricultural Science and Technology Indicators (ASTI): The International Food Policy Research Institute (IFPRI) collects and hosts data on government, higher education, nonprofit, and (where possible) private sector agricultural R&D investment in low- and middle-income countries.
  • Financial Inclusion Insights (FII): Collected and hosted by Intermedia, the FII surveys capture data on consumer financial behaviors, including trends in mobile money and other digital financial services. The FII includes nationally-representative cross-sections for multiple years for Bangladesh, India, Indonesia, Kenya, Nigeria, Pakistan, Tanzania and Uganda, and is currently expanding its scope to include Benin, Ghana, Rwanda, and Senegal.

Data Analysis Tips and Considerations: 

We have compiled a brief with a set of helpful tips and considerations for conducting data analyses, drawing from our research experience. These tips include notes on getting to know your dataset, practices for data cleaning, and preparing and organizing your code and the documentation for your analysis.

Resources for Research and Statistical Analysis: