De-climatizing food security: Lessons from climate change micro-simulations in Peru

Autoři: Gustavo Anríquez aff001;  Gabriela Toledo aff001
Působiště autorů: Pontificia Universidad Católica de Chile, Departamento de Economía Agraria, Facultad de Agronomía e Ingeniería Forestal, Santiago, Chile aff001;  Center for the Socioeconomic Impact of Environmental Policies, Santiago, Chile aff002
Vyšlo v časopise: PLoS ONE 14(9)
Kategorie: Research Article
doi: 10.1371/journal.pone.0222483


This paper brings advances in weather data collection and modeling, and developments in socioeconomic climate microsimulations to bear on the analysis of the implications of climate change (CC) in the design of public policies to combat food insecurity. It uses new downscaled predictions of future climate in 2050, derived from three Earth System Models calibrated with a new historical weather station dataset for Peru. This climate data is used in a three-stage socioeconomic microsimulation model that includes climate risk, and deals with the endogeneity of incomes and simultaneity of expected food consumption and its variability. We estimate the impact of CC on agricultural yields, and find results consistent and fully bounded within what the global simulations literature has found, with yields falling up to 13% in some regions. However, we show that these drops (and increases) in yields translate to much smaller changes in food consumption, and also surprisingly, to very minor impacts on vulnerability to food insecurity. The document explores what explains this surprising result, showing that in addition to characteristics that are specific to Peru, there are household and market mediating mechanisms that are available in all countries, which explain how changes in yields, and corresponding farm incomes have a reduced impact in vulnerability to food insecurity. Finally, in light of these findings, we explore which policies might have greater impact in reducing food insecurity in contexts of hunger prevalence.

Klíčová slova:

Agricultural workers – Agriculture – Climate change – Crops – Food consumption – Peru – Simulation and modeling – Climate modeling


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