Person:
Larson, Donald F.
Author Name Variants
Fields of Specialization
Rural Development Policy; Natural Resource Policy; Agricultural Productivity and Growth; Climate Change Policy and Markets; Commodity Markets and Risk
Degrees
External Links
Departments
Development Research Group, World Bank
Externally Hosted Work
Contact Information
Last updated
January 31, 2023
Biography
Donald F. Larson is a Senior Economist with the World Bank’s Development Research Group. He holds a B.A in economics from the College of William and Mary, an M.A. in economics from Virginia Tech, and a Ph.D. in Agricultural and Resource Economics from the University of Maryland.
With colleagues, he has authored or edited five books, including An African Green Revolution: Finding Ways to Boost Productivity on Small Farms, a forthcoming volume from Springer, and The Clean Development Mechanism: An Early History of Unanticipated Outcomes, a forthcoming volume from World Scientific. He has published numerous book chapters and journal articles, with an emphasis on agricultural productivity and growth; food and rural development policies; natural resource policies; the institutions and markets related to climate change; and the performance of commodity futures and risk markets.
During his time with the World Bank, Don has participated in policy discussion in Africa, Eastern Europe, Central Asia, East Asia, Latin America, and the Caribbean. He was a member of the team that launched the World Bank’s Prototype Carbon Fund.
Publication Search Results
1 - 2 of 2
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Publication
A Conceptual Model of Incomplete Markets and the Consequences for Technology Adoption Policies in Ethiopia
(World Bank, Washington, DC, 2013-10)In Africa, farmers have been reluctant to take up new varieties of staple crops developed to boost smallholder yields and rural incomes. Low fertilizer use is often mentioned as a proximate cause, but some believe the problem originates with incomplete input markets. As a remedy, African governments have introduced technology adoption programs with fertilizer subsidies as a core component. Still, the links between market performance and choices about using fertilizer are poorly articulated in empirical studies and policy discussions, making it difficult to judge whether the programs are expected to generate lasting benefits or to simply offset high fertilizer prices. This paper develops a conceptual model to show how choices made by agents supplying input services combine with household livelihood settings to generate heterogeneous decisions about fertilizer use. An applied model is estimated with data from a panel survey in rural Ethiopia. The results suggest that adverse market conditions limit the adoption of fertilizer-based technologies, especially among resource-poor households. Farmers appear to respond to market signals in the aggregate and this provides a pathway for subsidies to stimulate demand. However, the research suggests that lowering transaction costs, through investments in infrastructure and market institutions, can generate deeper effects by expanding the technologies available to farmers across all pricing outcomes. -
Publication
Should African Rural Development Strategies Depend on Smallholder Farms? An Exploration of the Inverse Productivity Hypothesis
(World Bank, Washington, DC, 2012-09)In Africa, most development strategies include efforts to improve the productivity of staple crops grown on smallholder farms. An underlying premise is that small farms are productive in the African context and that smallholders do not forgo economies of scale -- a premise supported by the often observed phenomenon that staple cereal yields decline as the scale of production increases. This paper explores a research design conundrum that encourages researchers who study the relationship between productivity and scale to use surveys with a narrow geographic reach, when policy would be better served with studies based on wide and heterogeneous settings. Using a model of endogenous technology choice, the authors explore the relationship between maize yields and scale using alternative data. Since rich descriptions of the decision environments that farmers face are needed to identify the applied technologies that generate the data, improvements in the location specificity of the data should reduce the likelihood of identification errors and biased estimates. However, the analysis finds that the inverse productivity hypothesis holds up well across a broad platform of data, despite obvious shortcomings with some components. It also finds surprising consistency in the estimated scale elasticities.