Aid for Sustainable Trade (AST) – Researching mechanisms and sustainability trade-offs

• Applicant: Dr. Lennart Kaplan
• Subject Area: Economic Policy, Applied Economics
• Term: since 2025
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 566624008

Current development policy increasingly targets private sector activities to promote commerce and achieve self-sustaining growth. For that purpose, the World Trade Organization has promoted Aid for Trade (AfT) as a tool to foster private economic activities via the provision of aid for (i) infrastructure, (ii) productive capacities, and (iii) trade policies and regulations. AfT accounts for approximately one-fourth of the global aid budget and addresses several of the United Nations’ Sustainable Development Goals (SDGs): SDG2 (Zero Hunger) through its effects on agriculture and food distribution, SDG7 (Affordable and Clean Energy) by supporting the energy transformation in recipient countries, and SDG9 (Industry, Innovation, and Infrastructure) through the promotion of productive capacities and infrastructure. However, there are also potential negative side effects of aid-induced trade, such as the politicization of aid, increased vulnerability of producers and consumers, and environmental externalities. Previous research at the country-level has shown mild trade effects from AfT. Yet, as impacts related to infrastructure and externalities are spatially dispersed, cross-country estimates may obscure part of these effects. To date, sub-national data has been underutilized in studying AfT, particularly since data for the European Union, which provides half of the global AfT budget, was so far not available at the sub-national, regional level. Against this backdrop, I pursue three key objectives in this project, providing sub-national and micro-level evidence on AfT. First, I will advance the literature through the use of novel data. I will extend data for the main AfT donors and re-code infrastructure projects at the sub-national level to match them to innovative data at the regional, firm, and farm levels. Additionally, I will compile micro data from a randomized control trial on how AfT improves agricultural production capacities and enhances transparency in value chains. Second, I will use these novel data to delve deeper into mechanisms of sub-national trade costs, differential producer and consumer effects, as well as the trust between buyers and sellers. Third, I will advance the literature in terms of causal estimates. Specifically, I will leverage the novel data to derive instrumental variable approaches that are augmented by machine-learning based selection bias correction. Moreover, the randomized controlled trial will provide causal evidence on how AfT affects farmers’ participation in trade networks.

• DFG Programme: Research Grants
• International Connection: Sweden, USA
• Cooperation Partners: Professor Dr. Adel Daoud; Professor Connor Jerzak