The fifth round of the Myanmar Household Welfare Survey (MHWS)–a nationwide phone panel consisting of 12,953 households–was implemented between March, 2023 and June, 2023.
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The sixth round of the MHWS was carried out between October 12, 2022, and December 30, 2022. In the fourth round, 12,924 households responded to the survey.
The 2019 Ghana Social Accounting Matrix (SAM) follows IFPRI's Standard Nexus SAM approach, by focusing on consistency, comparability, and transparency of data.
The 2019 Malawi Social Accounting Matrix (SAM) follows IFPRI's Standard Nexus SAM approach, by focusing on consistency, comparability, and transparency of data.
This document describes the steps involved in generating the value of production in the Ag-Incentives database.
The fourth round of the MHWS was carried out between October 12, 2022, and December 30, 2022. In the fourth round, 12,924 households responded to the survey.
Myanmar Agricultural Performance Survey Round Two: Note on Sample Characteristics and Weighting
Myanmar Agricultural Performance Survey (MAPS) Round 2 is a sub-sample survey carried out during the Dry (pre/post monsoon) Season of 2022 that includes farming households from the Myanmar Household Welfare Survey (MHWS).
Support to agriculture producers is provided in different forms, including border measures, domestic subsidies, and income transfers from taxpayers to producers.
Prior to the 1980s, information on agricultural incentives provided by governments was extremely limited and difficult to access. Much debate took place on the basis of participants’ preferred alternative facts.
The 2021 Kenya Social Accounting Matrix (SAM) follows IFPRI's Standard Nexus SAM approach, by focusing on consistency, comparability, and transparency of data.
The Nexus Project is a collaboration between IFPRI and its partners, including national statistical agencies and research institutions.
The 2021 Zambia Social Accounting Matrix (SAM) follows IFPRI's Standard Nexus SAM approach, by focusing on consistency, comparability, and transparency of data.
Policy makers, analysts, and civil society face increasing challenges to reducing hunger and sustainably improving food security. Modeling alternative future scenarios and assessing their outcomes can help inform policy choices.
Policy makers, analysts, and civil society face increasing challenges to reducing hunger and sustainably improving food security. Modeling alternative future scenarios and assessing their outcomes can help inform policy choices.
Policy makers, analysts, and civil society face increasing challenges to reducing hunger and sustainably improving food security. Modeling alternative future scenarios and assessing their outcomes can help inform policy choices.
This is the baseline dataset for the Farm and Family Balance Study. Sample consists of married sugarcane farmers associated with a large sugar company near Jinja, Uganda. All eligible farmers who agreed to participate are included.
This dataset is a follow-up for households who were visited during Feed the Future I (FtF) Ethiopia end-line Survey 2018 and who participated in land rental market in Tigray and Amhara regions.