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Spatial variation in fertilizer prices in Sub-Saharan Africa

Author: Bonilla Cedrez, C.
Author: Chamberlin, J.
Author: Guo, Z.
Author: Hijmans, R.J.
Year: 2020
ISSN: 1932-6203 (Print)
URI: https://hdl.handle.net/10883/20659
Format: PDF
Language: English
Publisher: Public Library of Science
Copyright: CIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose.
Type: Article
Place of Publication: San Francisco, CA (USA)
Issue: 1
Issue: art. e0227764
Volume: 15
DOI: 10.1371/journal.pone.0227764
Description: Low crop yields in Sub-Saharan Africa are associated with low fertilizer use. To better understand patterns of, and opportunities for, fertilizer use, location specific fertilizer price data may be relevant. We compiled local market price data for urea fertilizer, a source of inorganic nitrogen, in 1729 locations in eighteen countries in two regions (West and East Africa) from 2010–2018 to understand patterns in the spatial variation in fertilizer prices. The average national price was lowest in Ghana (0.80 USD kg-1), Kenya (0.97 USD kg-1), and Nigeria (0.99 USD kg-1). Urea was most expensive in three landlocked countries (Burundi: 1.51, Uganda: 1.49, and Burkina Faso: 1.49 USD kg-1). Our study uncovers considerable spatial variation in fertilizer prices within African countries. We show that in many countries this variation can be predicted for unsampled locations by fitting models of prices as a function of longitude, latitude, and additional predictor variables that capture aspects of market access, demand and environmental conditions. Predicted within-country urea price variation (as a fraction of the median price) was particularly high in Kenya (0.77–1.12), Nigeria (0.83–1.34), Senegal (0.73–1.40), Tanzania (0.90–1.29) and Uganda (0.93–1.30), but much lower in Burkina Faso (0.96–1.04), Burundi (0.95–1.05), and Togo (0.94–1.05). The correlation coefficient of the country level models was between 0.17 to 0.83 (mean 0.52) and the RMSE varies from 0.005 to 0.188 (mean 0.095). In 10 countries, predictions were at least 25% better than a null-model that assumes no spatial variation. Our work indicates new opportunities for incorporating spatial variation in prices into efforts to understand the profitability of agricultural technologies across rural areas in Sub-Saharan Africa.
Country of Focus: AFRICA SOUTH OF SAHARA
Agrovoc: FERTILIZERS
Agrovoc: MARKETS
Agrovoc: PRICES
Related Datasets: https://hdl.handle.net/10.7910/DVN/E0EHLO
Related Datasets: https://doi.org/10.1371/journal.pone.0227764.t001
Journal: PLoS ONE


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  • Socioeconomics
    Including topics such as farming systems, markets, impact & targeting, innovations, and GIS

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