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The Demand for Advice : Theory and Empirical Evidence from Farmers in Sub-Saharan Africa / Dominik Naeher.
World Bank Open Knowledge Repository (formerly "World Bank E-Library Publications") Available online
View online- Format:
- Book
- Government document
- Author/Creator:
- Naeher, Dominik.
- Series:
- Policy research working papers.
- World Bank e-Library.
- Language:
- English
- Subjects (All):
- Agricultural Extension.
- Agricultural Knowledge and Information Systems.
- Agriculture.
- Economic Development.
- Farmer.
- Information and Communication Technologies.
- Information Technology.
- Rational Inattention.
- Local Subjects:
- Agricultural Extension.
- Agricultural Knowledge and Information Systems.
- Agriculture.
- Economic Development.
- Farmer.
- Information and Communication Technologies.
- Information Technology.
- Rational Inattention.
- Physical Description:
- 1 online resource (61 pages)
- Other Title:
- Demand for Advice
- Place of Publication:
- Washington, D.C. : The World Bank, 2021.
- System Details:
- data file
- Summary:
- Low levels of investment into modern technologies, and limited use of measures that have low monetary cost but the potential for high yields, are often regarded as obstacles to further agricultural development. This paper investigates farmers' demand for one such measure, namely agricultural advisory services. These have modest (most frequently zero) monetary user cost but, according to some recent research, have the potential to result in large increases of yields. Yet, demand for these extension services is often low. This study proposes that costly attention may be part of the explanation for this. In the model, advisory services are available free of charge, but positive effects on production are only realized if farmers devote attention to listening to and implementing the provided advice. Modeling farmers as rational decision makers facing scarce attention, the study identifies the circumstances under which farmers may optimally abstain from demanding advisory services. The model complements the insights of other theories commonly used to explain suboptimal farm decisions and outcomes, and generates testable predictions, which are consistent with empirical evidence based on a large farm-level panel dataset from Sub-Saharan Africa.
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