Browsing by Author "Chingozha, Tawanda"
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- ItemLand rights in sub-Saharan Africa : measuring impact with satellite images, machine learning and citizen science(Stellenbosch : Stellenbosch University, 2020-03) Chingozha, Tawanda; Von Fintel, Dieter; Stellenbosch University. Faculty of Economic and Management Sciences. Dept. of Economics.ENGLISH ABSTRACT : The thesis employs satellite imagery to measure the impacts of land rights- in data-scarce sub-Saharan Africa (SSA). SSA governments are politically and financially constrained to provide objective and reliable research data at a reasonable spatial and temporal frequency. The thesis hence fills important data gaps. The research content highlights the importance of land tenure security enforcement and access to markets in rural SSA. It is widely acknowledged that colonial institutions, particularly private property rights, continue to affect modern development. Across SSA, the majority of people rely on agriculture as a source of livelihood. Hence, agriculture has an important role to play in alleviating poverty and inequality. A consequence of extractive colonial institutions is that they selectively introduced property rights, with the majority of indigenous farming in SSA remaining under customary tenure system. This system limits the extent to which there can be effective market participation. Low investments in public goods (in particular roads and railways) and the relatively poor quality of the land in these areas compounds the problem. Chapter 2 of the thesis investigates access to markets as an important pre-condition for land titles to affect agricultural growth. Using the case of Southern Rhodesia, we investigate whether land titles incentivised African large-scale holders in the Native Purchase Areas (NPAs) to put proportionally more of their available land under cultivation than their counterparts in the overcrowded Tribal Trust Areas (TTAs). We create a novel dataset by applying a Support Vector Machine (SVM) learning algorithm on Landsat imagery for the period 1972 to 1984 - the period during which the debate on the nexus between land rights and agricultural production intensified. Our results indicate that land titles are only beneficial when farmers are located closer to main cities, main roads and rail stations or sidings. In order to address past imbalances, SSA countries have attempted various reforms in the agricultural sector, including land redistribution and tenure reform. These reforms have not translated to agriculture growth; the main argument for stagnation post-reform is that governments do not follow through in enforcing property rights. Chapter 3 of the study focuses on Zimbabwe’s 2000 Fast Track Land Reform Program (FTLRP) that reallocated more than 80% of land previously held by Europeans to the African majority. We rely on a novel, countrywide dataset of the amount of land under cultivation and crop quality [Normalised Difference Vegetation Index (NDVI)] as the endogenous variables. No study has measured the national impact of the programme on agriculture. The wide scale of the FTLRP offers a unique opportunity to interrogate how incomplete property rights (enforced land titles) affect crop cultivation in SSA post land reform, within a natural experiment design. Our Difference-in- Difference (DID) and Spatial Regression Discontinuity (RDD) estimates suggest lack of follow-through. Land redistribution reduces crop cultivation and crop quality significantly. Measuring socio-economic change using remote-sensed data is also important within urban settings. The unplanned nature and unregistered status of commercial and residential informal establishments in urban SSA limit economic potential because of lack of land titles. Where settlements are unplanned and businesses are unregistered, trust lacks, land markets are imperfect and other opportunity costs arise. Owners or occupants cannot use informal establishments as collateral to access credit, for example. Informality also has direct costs if urban services and amenities buckle under pressure. High informality results from a migration rate that exceeds job creation in urban areas. Authorities can choose between destroying informal establishments and efficient urban planning and enforcing tenure security to manage urban densification. The latter requires the development of cadastral databases and land use maps – an exercise which may be costly and resource intensive. Chapter 4 investigates the use of citizen science to classify the informal sector and different land use types from Very High Resolution (VHR) satellite images. It explores the conditions or factors affecting the precision of generating land cover maps/cadastral databases through citizen science. Cost minimization should not significantly sacrifice quality. The chapter presents a pilot study with a group of 41 Stellenbosch University students, who volunteered to classify different land use types. We use a sample of satellite images before and after Operation Restore Order (ORO) (a 2005 clean-up operation that destroyed informal structures in Zimbabwe’s main urban areas). Estimates show that the higher the number of classifications, the better the precision axiom in accordance to Linus Law does not hold; possibly due to the irregular, small and sparsely distributed nature of informal structures. It is also shown that learning effect (experience and training), as well as the demographic variables of race, sex, nationality and student volunteer hands-on experience with the land use type in question are important factors affecting classification accuracy.