The SIEG project is run by Leandro de Magalhaes (U of Bristol), Pau Milán (MOVE-UAB and Barcelona GSE) and Raül Santaeulàlia-Llopis (MOVE-UAB and Barcelona GSE)

Overview

The goal of this project is to analyze the potential trade-offs between the provision of social insurance and productivity through village networks. If productive individuals within a village are subject to implicit progressive redistributive taxes, this can have pervasive implications for incentives to work, accumulate wealth, migrate, and ultimately grow. In our investigation we collect a new data set of consumption, income, and network information for a complete village in rural Malawi in order to keep track of the status quo redistributive tax/subsidy scheme and its relation to productivity within village.

Team

Apart from the three PI's, the team on-site is composed of Albert Rodríguez (Research Assistant at UAB) as well as members from a local research organization called Invest in Knowledge Initiative (IKI).  Specifically, we count with the support of Augustine Harawa (project manager) and Sydney Rodney Lungu (data manager), together with a team of trained enumerators, drivers, and translators. 

Questionnaire (First Wave: Sept. 2018)

We ask questions on consumption, income, and ex-ante (pre-harvest) allocation of resources (e.g., land and fertilizer).  We link these measures with ex-post (post-harvest) redistribution of agricultural output (e.g., food transfers along the village network). We also plan to link these measures to the ability of hosueholds of generating income, that is, agricultural productivity. The entire survey can be downloaded here. 

Summer School

The Barcelona GSE Summer School on Economic Development acquaints students with this particular project and allows students to participate in the implementation of new questionnaires for future waves of the survey. 

Funding

Field work currently funded by La Caixa Foundation Research Grants on Socioeconomic Wellbeing 2018. This initiative has also previously received funding from BGSE Seed Grants (SG-2017-02) and (SG-2017-04), and from European Research Council (ERC) under the European Union’s Seventh Framework Programme FP7/2007-2013 GA number 324048-(APMPAL) and Horizon2020 GA number 788547 (APMPAL-HET).