Abstract

Poverty alleviation is an important objective of horticultural projects in developing countries. Impacts have to be reported to funders, and create need for credible impact assessments. The ways to measure these changes and translate these into impact estimates need careful design, considering the counterfactual. Impact attribution is especially difficult in private ventures that target poor households with technologies that are incorporated in strategies of the poor as producers. These items are sold through market channels and become part of a wider set of factors that create the poverty impact. We tested a quasi-experimental method for assessing changes in household income and attribute it to technology adoption. The ‘Rolling Baseline Survey Methodology’, was developed and applied in Zambia, Ethiopia and Nepal by IDE, a non-profit organization that develops and promotes market-based supply chains of low-cost micro-irrigation equipment for poor households. Household income changes are calculated yearly by estimating the respondent’s net cash income from farm-based activities, before and after technology adoption. Pre-adoption household incomes of the successive cohort are used to construct the counterfactual, a proxy control for exogenous factors such as price fluctuations and weather conditions. This paper describes the application of the rolling baseline methodology and the ways to control for selection bias and recall bias. The paper reports average first-year treatment effects of irrigation-induced horticultural development measured as additional household cash income.

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