Whole-farm Model: Detailed Data on Nine Farms for Impact Assessment of Africa RISING Technologies

The zip.file contains the Farm DESIGN model (software) as well as the input data. A user manual of the software can be found online. The zipped Farm DESIGN model contains the whole-farm representation of nine farms in Northern Ghana. A low, medium and a high resource endowed farm per site, namely in Duko (Northern Region), Nyangua (Upper East) and Zanko (Upper West). There are several models per farm:


1. The current/ actual farm configuration

2. The baseline (reset to a situation with traditional (no Africa RISING) farming practices)

3. The farm, where Africa RISING Package 1 (Maize) is implemented

4. The farm, where Africa RISING Package 2 (Cowpea) is implemented

5. The farm, where Africa RISING Package 3 (Soybean) is implemented

6. The farm, where Africa RISING Package 4 (Maize-Legume Rotation) is implemented

7. The farm, where Africa RISING Package 5 (Maize-Legume Strip Crop) is implemented

8. A farm-model that is ready for an exploration (containing additional options the model may choose)

Replication Data for: Trade-Offs and Synergies Between Yield, Labor, Profit, and Risk in Malawian Maize-Based Cropping Systems

As part of an IFPRI-led study, raw and partially processed secondary data have been harmonized and analyzed to examine the ex-ante effects of different legume and fertilizer practices on cropping systems indicators for maize-based smallholder farmers in the Golomoti Extension Planning Area of central Malawi. The current dataset contains the data files and code needed to replicate the results presented in the publication “Trade-Offs and Synergies Between Yield, Labor, Profit, and Risk in Malawian Maize-Based Cropping Systems.”

Household survey data collected as part of the Africa Research In Sustainable Intensification for the Next Generation (Africa RISING) program, along with secondary data from journal articles and the Malawian Agricultural Market Information System, as well as other biophysical and economic data have been harmonized and analyzed using Stata. Stata do files have been created for data processing and analysis as noted in the “Documentation” file included in this study.


This work was undertaken as part of, and funded by, the CGIAR Research Program on Policies, Institutions, and Markets (PIM) led by the International Food Policy Research Institute (IFPRI). PIM is in turn supported by the CGIAR Fund donors. The HarvestChoice Project, funded by the Bill and Melinda Gates Foundation, also funded this study. The United States Agency for International Development funded the collection of the household survey data, as part of the Africa RISING program.