Thou shalt be given… but how? A replication study and extended cost-effectiveness analysis of a randomized experiment on food assistance in Northern Ecuador. Issue 4 (2nd October 2019)

• Record Type: Journal Article
• Authors: Lhachimi, Stefan K.; Seuring, Till
• Is Part Of: Journal of development effectiveness. Volume 11:Issue 4(2019)
• Page Start: 373
• Page End: 390
• Publication Date: 2019-10-02
• Subjects: Replication -- food assistance -- cost-effectiveness -- uncertainty; Economic development -- Periodicals; Developing countries -- Economic conditions -- Periodicals; Economic development; Economic history; Developing countries; Periodicals; 338.91724
• DOI: 10.1080/19439342.2019.1666901
• Languages: English
• ISSNs: 1943-9342

Abstract

ABSTRACT: The original cluster-randomised controlled trial took place in two provinces of Northern Ecuador. The trial compared cash, food or voucher assistance and found them to be effective. The results of the original paper are completely replicable and the findings of the original analysis are robust; however, we additionally find that treatments are more effective in the poorer province. We then extend the cost-effectiveness analysis by taking into account the parameter uncertainty in a probabilistic sensitivity analysis (PSA). Moreover, we provide information about the usefulness of additional research to reduce uncertainty concerning the cost-effectiveness analysis by calculating the expected value of perfect information (EVPI). Our extended cost-effectiveness analysis reveals that for some outcomes decision makers with a relatively small willingness-to-pay maybe a risk to choose a less cost-effective intervention. Furthermore, our findings indicate that further research into the comparative cost-effectiveness of these interventions could be worthwhile. This is in particular true for low-resource settings where decision makers face stricter budget constraints to finance interventions. In particular, policy makers with a small budget have a high risk of choosing a comparably less cost-effective treatment. Hence, further research to reduce uncertainty of effect estimates could aid decision-making.