Project description
Climate change impacts on developing countries' agriculture
In developing countries, agricultural productivity is lower compared to other sectors, and there is a significant disparity in productivity across space, raising questions about the continued engagement of workers in agriculture. Rural areas, where a substantial percentage of the population resides, encounter challenges such as agricultural risks and poverty. The ERC-funded RUSTDEC project seeks to elucidate the agricultural productivity gap in Sub-Saharan Africa and Southeast Asia. To that end, it will use innovative micro-panel data alongside geospatial data and theoretical models. The project's objectives include identifying the determinants of agricultural productivity, the microeconomic dynamics of labour reallocation and skill selectivity, as well as the impact of climate change on agricultural production and rural development.
Objective
A key feature of economic development is structural transformation characterized by spatial and sectoral labor reallocation out of agriculture. Despite clear evidence of rural-urban migration flows in developing countries, recent contributions show persistently lower productivity in agriculture compared to other sectors and large disparity in agricultural productivity across space. This points to the key question of this proposal: “why do so many workers remain in agriculture”? There is a pressing need for reliable answers to this question as rural areas host large shares of the population, facing high agricultural risk and poverty incidence. Any effective poverty eradication policy, such as those envisioned by the UN’s Sustainable Development Goals, must therefore necessarily focus on rural development. RUSTDEC will obtain novel answers to this key question by combining innovative micro panel data from Sub-Saharan Africa and Southeast Asia with an array of geospatial data on rural areas, exogenous variation in agricultural productivity, and quantitative theoretical models. The project employs remote-sensing and computer vision methods for generating community data as well as quasi-experimental and structural estimation techniques for rigorous causal estimation to pursue three major objectives: (i) provide first evidence on the role of dynamic adjustments in agricultural production for explaining the agricultural productivity gap and the magnitude of factor (mis-)allocation; (ii) dissect the microeconomic anatomy of spatial and sectoral labor reallocation and skill selectivity within and across rural communities; and (iii) identify the historic and future impact of climate change on agricultural production, adaptation, and rural development and its implications for the productivity gap. These objectives address three well-defined gaps in the literature, each going beyond the specific state-of-the-art and with the potential of generating ground-breaking impact.
Fields of science
- medical and health sciencesbasic medicineanatomy and morphology
- natural sciencescomputer and information sciencesartificial intelligencecomputer vision
- social scienceseconomics and businesseconomicsproduction economicsproductivity
- agricultural sciencesagriculture, forestry, and fisheriesagriculture
- natural sciencesearth and related environmental sciencesatmospheric sciencesclimatologyclimatic changes
Keywords
Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Topic(s)
Funding Scheme
HORIZON-ERC - HORIZON ERC GrantsHost institution
08005 Barcelona
Spain
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.