Publication: Agriculture Production and Transport Infrastructure in East Africa: An Application of Spatial Autoregression
Date
2015-06
ISSN
Published
2015-06
Author(s)
Abstract
Africa is estimated to have great
potential for agricultural production, but there are a
number of constraints inhibiting the development of that
potential. Spatial data are increasingly important in the
realization of potential as well as the associated
constraints. With crop production data generated at 5-minute
spatial resolution, the paper applies the spatial tobit
regression model to estimate the possible impacts of
improvements in transport accessibility in East Africa. It
is found that rural accessibility and access to markets are
important to increase agricultural production. In particular
for export crops, such as coffee, tea, tobacco, and cotton,
access to ports is crucial. The elasticities are estimated
at 0.3–4.6. In addition, the estimation results show that
spatial autocorrelation matters to the estimation results.
While a random shock in a particular locality would likely
affect its neighboring places, the spatial autoregressive
term can be positive or negative, depending on how
fragmented the current production areas are.
Link to Data Set
Citation
“Iimi, Atsushi; You, Liangzhi; Wood-Sichra, Ulrike; Humphrey, Richard Martin. 2015. Agriculture Production and Transport Infrastructure in East Africa: An Application of Spatial Autoregression. © World Bank, Washington, DC. http://hdl.handle.net/10986/22154 License: CC BY 3.0 IGO.”
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