Pulse Brain · Growing Health Evidence Index
Tier 3 — Observational / field trialPeer-reviewedConventional

Impact of Non-Farm Enterprises on Household Poverty Status: A Propensity Score Matching Approach

John Bosco Asiimwe; Steven Katende; Claire Ashaba

Journal of Poverty · 2025

Read source ↗ All evidence

Summary

This study uses propensity score matching applied to nationally representative household survey data (2016/17 and 2019/20) to evaluate how participation in non-farm enterprises affects poverty status in Uganda. The analysis found that NFE participation reduced poverty incidence substantially, with participating households 8% and 6% more likely to be non-poor in the two survey periods respectively, and that benefits were largest for rural and low-income households. The findings suggest NFEs play an important role in household income diversification and poverty reduction, though regional disparities persist.

Regional applicability

This research is specific to Uganda's context and policy environment. Findings may have limited direct transferability to United Kingdom conditions, where agricultural diversification and off-farm income strategies operate within different institutional, market, and regulatory frameworks. However, the methodological approach (propensity score matching to evaluate income diversification interventions) could inform similar impact evaluations in other low- and middle-income country settings.

Key measures

Poverty incidence (probability of non-poor status); household expenditure; income mobility; regional and income-stratified sub-group analysis

Outcomes reported

The study measured the impact of non-farm enterprise (NFE) participation on household poverty status, income mobility, and expenditure patterns. It quantified the probability of households achieving non-poor status and identified differential benefits across rural, urban, and income-stratified populations.

Theme
Policy, governance & rights
Subject
Food security & global nutrition
Study type
Research
Study design
Observational cohort with propensity score matching
Source type
Peer-reviewed study
Status
Published
Geography
Uganda
System type
Food supply chain
DOI
10.1080/10875549.2025.2467622
Catalogue ID
NRmu58s0es-00d

Topic tags

Pulse AI · ask about this record

Dig deeper with Pulse AI.

Ask about this record, its theme or its relevance to UK farming and policy. Pulse AI uses selected catalogue evidence and cites the sources it draws on.