Strategic agricultural development policy and investment studies make growing use of geo-referenced data and spatial methods. Spatial perspectives provide intuitive entry points for examining the performance of agriculture, a physically-extensive, economic undertaking that owes much to spatial patterns of natural and human-endowed assets. The research described in this thesis responds to a conjuncture of three issues: a growing demand for development policy and investment support that recognizes and accounts for the heterogeneity of development conditions in a national and regional (cross-country) context; the increasing supply and utility of spatial information, including the geo-coding of community and household survey data, that open up the possibility of new, spatially-enriched approaches to strategic development analysis; and the need to provide improved theoretical frameworks, conceptual approaches, and empirical validation, especially those driven by an economics perspective, such that the growing demand meets the increasing supply in credible and effective ways. Specifically, the research tests the notion that regional, geo-referenced data on agricultural potential, population density, and market access, used alone, can provide significant explanatory power in accounting for observed variability in key economic characteristics of crop-based livelihoods, such as input use, productivity, market participation and output value. In setting out to achieve that goal I construct a theoretical framework that formally integrates the land quality, population pressure and market distance principles of Ricardo, Boserup and von Thiinen respectively. I also examine how the empirical explanatory variables perform in representing the conceptual variables of the theory. I develop and apply some innovative empirical variables - not always with success, and provide illustrations of spatial predictions of crop strategies based on application of the theory-based model, as well of geographically-explicit regression. In all these analyses I hold the regional location attribute (GIS) explanatory data to account against household and community data from the 1999-2000 Uganda National Household Survey.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:485700 |
| Date | January 2007 |
| Creators | Wood, Stanley Ronald |
| Publisher | University of London |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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