Journal of Agricultural and Resource Economics

This paper investigates the dynamic and spatial determinants of the distribution of agricultural productivity around the world, with a focus on the effects of climate on production risk. Distinguishing between climate and weather, the analysis is based on an exante approach where we treat weather shocks as part of the error term and proceed evaluating the probability distribution of agricultural productivity conditional on climate. The econometric analysis relies on a two-step approach: 1) a quantile autoregression (QAR) model representing the dynamics of the distribution of agricultural productivity; and 2) a copula capturing the spatial distribution of productivity across countries. The analysis is applied to the evolution of agricultural productivity (as measured by a TFP measure) in 160 countries over the period 1961-2016. We document that higher temperatures lead to large increases in production risk in agriculture. The adverse effects of higher temperature are found to be more severe in countries exhibiting low agricultural productivity. We show how the spatial codependence of production risk varies across latitude and longitude. The negative codependence across countries means that spatial diversification tends to reduce food insecurity at the world level. This effect contributes to dimming the adverse effects of rising temperatures on world food insecurity.

Publication Details

Journal
VTechWorks (Virginia Tech)
Published
2024-12-17
Primary Topic
Climate change impacts on agriculture
Type
article
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article

Journal of Agricultural and Resource Economics

VTechWorks (Virginia Tech)
Climate change impacts on agriculture
article

Journal of Agricultural and Resource Economics

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Abstract

This paper investigates the dynamic and spatial determinants of the distribution of agricultural productivity around the world, with a focus on the effects of climate on production risk. Distinguishing between climate and weather, the analysis is based on an exante approach where we treat weather shocks as part of the error term and proceed evaluating the probability distribution of agricultural productivity conditional on climate. The econometric analysis relies on a two-step approach: 1) a quantile autoregression (QAR) model representing the dynamics of the distribution of agricultural productivity; and 2) a copula capturing the spatial distribution of productivity across countries. The analysis is applied to the evolution of agricultural productivity (as measured by a TFP measure) in 160 countries over the period 1961-2016. We document that higher temperatures lead to large increases in production risk in agriculture. The adverse effects of higher temperature are found to be more severe in countries exhibiting low agricultural productivity. We show how the spatial codependence of production risk varies across latitude and longitude. The negative codependence across countries means that spatial diversification tends to reduce food insecurity at the world level. This effect contributes to dimming the adverse effects of rising temperatures on world food insecurity.

VTechWorks (Virginia Tech)
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Climate change impacts on agriculture
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