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Aggregation of Gridded Emulated Rainfed Crop Yield Projections at the National or Regional Level

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  • Elodie Blanc

Abstract

To estimate the impact of climate change on yields, researchers traditionally use process-based models or statistical models. To benefit from the capabilities of processed-based models while preserving the application simplicity of statistical models, Blanc and Sultan (2015) and Blanc (2017) provide an ensemble of statistical tools emulating crops yields from global gridded crop models at the grid cell level using a simple set of environmental variables. This paper and companion code provide a tool for researcher to use those statistical emulators and estimate crop yields of rainfed maize, rice, soybean and wheat at the regional level. Crop yields estimates for various regional delineations can them simply be used as input into a variety of numerical equilibrium models and other analyses.

Suggested Citation

  • Elodie Blanc, 2017. "Aggregation of Gridded Emulated Rainfed Crop Yield Projections at the National or Regional Level," Journal of Global Economic Analysis, Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University, vol. 2(2), pages 112-127, December.
    • Handle: RePEc:gta:jnlgea:v:2:y:2017:i:2:p:112-127
    DOI: http://dx.doi.org/10.21642/JGEA.020203AF
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    References listed on IDEAS

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    1. Elodie Blanc & Eric Strobl, 2013. "The impact of climate change on cropland productivity: evidence from satellite based products at the river basin scale in Africa," Climatic Change, Springer, vol. 117(4), pages 873-890, April.
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    Cited by:

    1. Wojtek Szewczyk & Luc Feyen & Anca Matei & Juan Carlos Ciscar & Eamonn Mulholland & Antonio Soria, 2020. "Economic analysis of selected climate impacts. JRC PESETA IV project –Task 14," JRC Research Reports JRC120452, Joint Research Centre.

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    Keywords

    Crop yields; Climate change;

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