Periodic Reporting for period 2 - RTSC (Rural transformation and structural change – A new spatial perspective on trade-offs in household decision-making in low-income countries)
Periodo di rendicontazione: 2023-09-01 al 2024-08-31
Understanding the decision-making of smallholder households in low-income countries is a crucial step in the design of effective policy measures for development. This task is becoming increasingly complicated as more and more factors (e.g. urbanization, climate change, conflict) influence rural transformation processes. Economic research normally singles out individual mechanisms (e.g. income composition) and spatial variability thereof is represented by access to the most important economic center in a region. However, trade-offs between multiple decision factors can lead to complex spatial patterns in livelihoods, often further complicated by multiple accessible economic centers. RTSC proposes an innovative and interdisciplinary framework to capture such complex patterns by modeling decision-making based on the location of a household in two-dimensional space. Among the objectives of the project are the development of microeconomic models capturing location-dependent trade-offs in household decision-making, the application of advanced statistical techniques to model potential nonlinearities, and the use of project results to support evidence-based policy design. All empirical analyses are conducted using primary data from Myanmar.
A large share of the work conducted in the project so far has been the processing of nationally representative survey data of agricultural and rural households in Myanmar collected by the International Food Policy Research Institute (IFPRI). This also includes the preparation of supplementary secondary and geospatial datasets to capture climate and weather variables, conflict events, and remoteness indicators. Based on these data sources several analyses are currently ongoing, addressing research questions around, for example, the effect of conflict on the rural-urban gradient of agricultural development, households' coping strategies when simultaneously facing climate and conflict shocks, and welfare trade-offs between livelihood diversification and specialization.
In a first working paper (https://www.ifpri.org/publication/urban-proximity-conflict-and-agricultural-development-evidence-myanmar) the empirical results indicate that the effect of conflict on agricultural development (e.g. input use, yield, prices) in Myanmar varies in space. That is, households in direct urban proximity or remote areas are disproportionately affected. Remote households are often relatively poor. Thus, conflict exacerbates already poor living conditions widening welfare gaps within the country. Households in urban proximity (i.e. with good market access) have been shown to modernize their production systems more easily and, therefore, drive agricultural development in the country. Conflict appears to be diminishing this comparative advantage of improved market access with likely serious consequences for economic development and food production in Myanmar.
In a first working paper (https://www.ifpri.org/publication/urban-proximity-conflict-and-agricultural-development-evidence-myanmar) the empirical results indicate that the effect of conflict on agricultural development (e.g. input use, yield, prices) in Myanmar varies in space. That is, households in direct urban proximity or remote areas are disproportionately affected. Remote households are often relatively poor. Thus, conflict exacerbates already poor living conditions widening welfare gaps within the country. Households in urban proximity (i.e. with good market access) have been shown to modernize their production systems more easily and, therefore, drive agricultural development in the country. Conflict appears to be diminishing this comparative advantage of improved market access with likely serious consequences for economic development and food production in Myanmar.
The results of the first research paper of the project already show that the specific location in space/on a remoteness gradient is a crucial factor in understanding the dynamics of rural transformation processes and welfare implications. This observation is also likely to be confirmed by the upcoming research outputs of the project. The researchers expect that these insights will be helpful to policymakers and stakeholders, emphasizing that spatially explicit analysis can improve the targeting of programs and interventions for a more effective allocation of resources.