3.8 Article

State-conditioned soil investment in rural Uganda

Journal

RESEARCH IN ECONOMICS
Volume 71, Issue 2, Pages 254-281

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.rie.2017.02.003

Keywords

Soil fertility; Soil investment; Starting conditions; Mixed integer programming

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While poor soils limit agricultural production across rural, sub-Saharan Africa, most small-holder farmers fail to invest in their soils in the way that soil scientists and policy makers prescribe. A small but growing literature examines biophysical constraints on soil investment, and in particular state-conditioned soil investment-the manner in which current soil fertility drives investment in soils in poor, agricultural contexts. While some research finds that farmers invest more in low fertility soils, other authors find the opposite. We model two types of state-conditioned soil investment, and show that while organic amendments in the form of manure or compost are optimally applied on low fertility plots, structural investments to halt soil degradation may not be optimal on any plots, or may be optimal only on high value, high fertility plots. Using plot-level panel data from Uganda, we find that soil fertility measures from 2003 do predict subsequent soil management practices a decade later. Farmers are more likely to apply organic amendments to low fertility plots, as predicted by our analytical model. Laborious conservation practices and structural investments in plots are quite rare, indicating that these measure may not be effective enough to be profitable in Uganda. Even so, certain conservation practices are predicted by 2003 soil fertility conditions. These associations, and the associations regarding organic amendment, are highly stable in the face of many controls-it appears that soils starting conditions do matter for subsequent soil investment decisions and soil fertility trajectories. Together, the model and empirical investigation bring nuance to the previous discussion on state-conditioned soil investment, and help to resolve seemingly inconsistent empirical findings in the literature. (C) 2017 University of Venice. Published by Elsevier Ltd. All rights reserved.

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