Fertilizer profitability for smallholder maize farmers in Tanzania: A spatially-explicit ex ante analysis

Sebastian Palmas and Jordan Chamberlin ()

PLOS ONE, 2020, vol. 15, issue 9, 1-16

Abstract: We present an easily calibrated spatial modeling framework for estimating location-specific fertilizer responses, using smallholder maize farming in Tanzania as a case study. By incorporating spatially varying input and output prices, we predict the expected profitability for a location-specific smallholder farmer. A stochastic rainfall component of the model allows us to quantify the uncertainty around expected economic returns. The resulting mapped estimates of expected profitability and uncertainty are good predictors of actual smallholder fertilizer usage in nationally representative household survey data. The integration of agronomic and economic information in our framework makes it a powerful tool for spatially explicit targeting of agricultural technologies and complementary investments, as well as estimating returns to investments at multiple scales.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0239149

DOI: 10.1371/journal.pone.0239149

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