Integrated spatial modeling of fertilizer investment returns to guide strategic investments : Application of a spatial ex ante analytical framework to smallholder maize production in Nigeria
Material type: TextLanguage: English Publication details: [Place of publication not identified] : EIA, 2024.Description: 18 pagesSubject(s): Online resources: Summary: Sustainably increasing the low rates of inorganic fertilizer use by smallholder farmers is a primary policy objective in Sub-Saharan Africa. Recognized constraints to fertilizer usage by resource-constrained and risk-averse farmers include (i) overly generalized recommendations, (ii) recommended application rates which are not profitable, and (iii) riskiness of productive investments in rainfed farming systems. To better identify and address these constraints, we describe a spatially-explicit modeling framework which uses empirical yield response data distributed across time and space to estimate the agronomic and economic returns to fertilizer investments. A novel feature of our framework is the formal incorporation of stochastic production outcomes, which allows us to model the riskiness of returns. We illustrate the application of this framework with data on maize farming in Nigeria. We also show how model results can be used to frame intervention areas for policy and investment programming designed to improve agricultural productivity through increased fertilizer usage.Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
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Report | CIMMYT Knowledge Center: John Woolston Library | CIMMYT Staff Publications Collection | Available |
Open Access
Sustainably increasing the low rates of inorganic fertilizer use by smallholder farmers is a primary policy objective in Sub-Saharan Africa. Recognized constraints to fertilizer usage by resource-constrained and risk-averse farmers include (i) overly generalized recommendations, (ii) recommended application rates which are not profitable, and (iii) riskiness of productive investments in rainfed farming systems. To better identify and address these constraints, we describe a spatially-explicit modeling framework which uses empirical yield response data distributed across time and space to estimate the agronomic and economic returns to fertilizer investments. A novel feature of our framework is the formal incorporation of stochastic production outcomes, which allows us to model the riskiness of returns. We illustrate the application of this framework with data on maize farming in Nigeria. We also show how model results can be used to frame intervention areas for policy and investment programming designed to improve agricultural productivity through increased fertilizer usage.
Text in English
Bonilla Cedrez, C.M. : No CIMMYT Affiliation