The thesis analyses spatial dependence in dyadic data by the means of three applications. These have in common that they concern bilateral international relations or flows between two countries with a particular focus on the relationship between developing and developed countries. While the first chapter provides a general introduction to spatial dependence with a focus on dyadic datasets, the second chapter looks at double taxation treaties (DTTs) and analyses whether strategic interaction among capital importing countries can explain the widespread conclusion of double taxation treaties between an industrialised and a developing country. This is important since upon entering such a treaty, the net-capital importer can lose a significant amount of tax revenues from foreign direct investment (FDI), while the net-capital exporter is better off. The analysis reveals that a country is more likely to enter a DTT if competitor countries for FDI also negotiated such a DTT, providing evidence for the hypothesis that the group of net-capital importers finds itself in a situation which can be described as a prisoners’ dilemma: individually they would be better off if they refused to negotiate a treaty, but collectively they have an incentive to sign such a tax treaty. The third chapter is on official development assistance and deals with the question whether a specific donor tends to dedicate a larger share of its aid budget to a certain recipient if other donors give money to the same beneficiary. A considerable degree of spatial dependence is found in the form that donors tend to allocate their money to the same recipients. Donors particularly follow the example of the most important aid donors. This behaviour has negative implications for aid effectiveness, contributes to harmful aid volatility and leads to aid darlings and orphans. However, there is no evidence that donors strategically interact with each other in order to pursue their military strategic and economic goals. Spatial dependence in asylum migration is the third application, discussed in the fourth chapter. It is well documented in the literature that personal networks of migrants reduce the risk of migration and facilitate transition to the host country. So far it has always been assumed that these personal networks only exist for fellow countrymen. The empirical analysis, however, shows that the positive effects also operate across borders and that also migrants from other geographically close source countries make asylum migration from a given source country more likely. Furthermore, it is shown that a more restrictive asylum policy in one destination country provides a negative externality for other destinations. This is because asylum seekers are deflected by a tighter asylum regime and encouraged to lodge their application in more liberal target countries.

This thesis explores how tourism policy, if based on evidence, can contribute to the objective of destination competitiveness. Evidence-based policy-making is informed by high-quality research formulated using rigorous, scientific methods. The thesis aims to show that policy analysis applied to the macro and micro levels can create evidence for use in policy formulation. The research is set within the Mediterranean context, with particular emphasis on Malta’s competitiveness within the inclusive tour holiday market originating from the United Kingdom. Using economic theory and econometrics, the thesis demonstrates the potential usefulness of econometric modelling in conducting such policy analysis. This is done by firstly estimating the effect of the Maltese government’s policy to subsidise tour operators on a set of destinations’ price and income elasticities, given that elasticities are deemed to be a good measure of destination competitiveness. These estimates are carried out through the application of the Almost Ideal Demand System model. Secondly, the price competitiveness of inclusive tour holidays is examined by applying the characteristics theory of value and the hedonic pricing model. The effect on package prices of inclusive tour holiday characteristics and of macroeconomic variables, including destinations’ relative prices, is quantified. The effect of the subsidisation policy is also estimated. The policy analysis results are then interpreted against the destination competitiveness frameworks. The implications for government policies and those of firms are discussed in relation to how destination competitiveness in the inclusive tour holiday market can accordingly be achieved through evidence-based policies. The findings clearly indicate that destinations can benefit significantly in terms of competitiveness by adopting an evidence-based approach to tourism policy-making. It is shown that government and the private sector have a key role to play for destinations to achieve competitiveness through the policies they adopt, highlighting the importance of informed and strategic approaches to governance.

Spatial data is a vital national resource necessary for a country’s efficient and sustainable economic, social and environmental development, and so must be properly developed and managed. In the Kingdom of Saudi Arabia (KSA), there is lack of knowledge and no clear framework describing the optimal way for stakeholders, users, providers or administrators, to collaborate effectively in establishing a National Spatial Data Infrastructure (NSDI). Moreover, the complex, multi-layer and multi-jurisdiction system of government leads to competing interests and mandates in coordinating spatial activity. Previous studies on NSDI in KSA focused on technical infrastructure strategy. However, there is a need to study institutional/organisational issues affecting collaboration in NSDI for KSA. This research presented in this thesis leads to recommendations for a best practice, collaboration initiative for Saudi NSDI, and contributes to advancing the goals and implementation of NSDI in KSA. A mixed (triangulated) quantitative and qualitative case study research design was adopted to assist in achieving the research aims, utilising a questionnaire and semi-structured interviews. The data was analysed and elicited concepts to recommend the Saudi NSDI collaboration initiative. A literature review was conducted in areas relevant to Spatial Data Infrastructure (SDI) and collaboration. The diverse definitions for SDI, its main components, and hierarchical nature were explored. Definitions for collaboration, motivational factors, and potential risks and costs were also reviewed. While a conventional NSDI is characterised by a top down approach, new technologies connected to social developments have led to a rapid, parallel development of commercial-, and consumer-led SDI, or dynamic ‘GeoWeb’, representing the potential next generation, Web 2.0 form, of NSDI. Institutional and technical factors are key elements in the success of NSDI collaboration initiatives, which include organisational commitment, policies, and technological resources. The national initiatives for the UK, USA, Australia, and Canada are reviewed and compared, along five key themes: objectives and vision, coordination, datasets, standards, and access. This highlighted the evolving nature of NSDI, given the rapid pace of developments in technology-driven applications and tools, and that coordination and agreement among all stakeholders requires accurate and reliable datasets, widely accepted metadata and standards, and interoperable technology, and must include all government levels and jurisdictions, with greater private sector integration. The current situation in KSA regarding the main SDI stakeholders, and their historical development, including legislation and policies and the barriers to sharing spatial data existing, facilitates background to understanding the issues involved in developing a Saudi NSDI. This is reinforced by primary data collected through a quantitative questionnaire survey of all 26 spatial data bodies in KSA, and qualitative semi-structured interviews of 72 key persons. The data includes themes, like types of spatial organisation and sphere of operations, data types and themes, standards and technical issues, and inter-organisational relationships and collaboration. The results revealed a lack of collaboration due to negative organisational cultures, and technical obstacles relating to a need for unified spatial data and metadata standards and specifications. In particular, there was an absence of appropriate legislation to deal with the two previous points, as well as providing protection for intellectual property; such legislation would outline a system within which collaboration would take place. The historical development and current status of key, independent SDI initiatives in KSA, i.e. MOMRA, Riyadh, and Saudi National SDI, are presented using data from secondary and primary sources. Each initiative represents city, ministry, and national level SDI initiative for collaboration. Finally, this research concludes by providing recommendations for best practice in collaboration among the various stakeholders forming a potential Saudi NSDI. It also outlines suggestions for future work.

Super-resolution mapping is becoming an increasing important technique in remote sensing for land cover mapping at a sub-pixel scale from coarse spatial resolution imagery. The potential of this technique could increase the value of the low cost coarse spatial resolution imagery. Among many types of land cover patches that can be represented by the super-resolution mapping, the prediction of patches smaller than an image pixel is one of the most difficult. This is because of the lack of information on the existence and spatial extend of the small land cover patches. Another difficult problem is to represent the location of small patches accurately. This thesis focuses on the potential of super-resolution mapping for accurate land cover mapping, with particular emphasis on the mapping of small patches. Popular super-resolution mapping techniques such as pixel swapping and the Hopfield neural network are used as well as a new method proposed. Using a Hopfield neural network (HNN) for super-resolution mapping, the best parameters and configuration to represent land cover patches of different sizes, shapes and mosaics are investigated. In addition, it also shown how a fusion of time series coarse spatial resolution imagery, such as daily MODIS 250 m images, can aid the determination of small land cover patch locations, thus reducing the spatial variability of the representation of such patches. Results of the improved HNN using a time series images are evaluated in a series of assessments, and demonstrated to be superior in terms of mapping accuracy than that of the standard techniques. A novel super-resolution mapping technique based on halftoning concept is presented as an alternative solution for the super-resolution mapping. This new technique is able to represent more land cover patches than the standard techniques.

The insurance industry is becoming increasingly exposed to the adverse impacts of climate variability and climate change. In developing policies and adapting strategies to better manage climate risk, insurers and reinsurers are therefore engaging directly with the climate modelling community to further understand the predictive capabilities of climate models and to develop techniques to utilise climate model output. With an inherent interest in the present and future frequency and magnitude of extreme climate-related loss events, insurers rely on the climate modelling community to provide informative model projections at the relevant spatial and temporal scales for insurance decisions. Furthermore, given the high economic stakes associated with enacting strategies to address climate change, it is essential that climate model experiments are designed to thoroughly explore the multiple sources of uncertainty. Determining the reliability of model based projections is a precursor to examining their relevance to the insurance industry and more widely to the climate change adaptation community. Designing experiments which adequately account for uncertainty therefore requires careful consideration of the nonlinear and chaotic properties of the climate system. Using the well developed concepts of dynamical systems theory, simple nonlinear chaotic systems are investigated to further understand what is meant by climate under climate change. The thesis questions the conventional paradigm in which long-term climate prediction is treated purely as a boundary value problem (predictability of the second kind). Using simple climate-like models to draw analogies to the climate system, results are presented which support the emerging view that climate prediction ought to be treated as both an initial value problem and a boundary condition problem on all time scales. The research also examines the application of the ergodic assumption in climate modelling and climate change adaptation decisions. By using idealised model experiments, situations in which the ergodic assumption breaks down are illustrated. Consideration is given to alternative model experimental designs which do not rely on the assumption of ergodicity. Experimental results are presented which support the view that large initial condition ensembles are required to detail the changing distribution of climate under altered forcing conditions. It is argued that the role of chaos and nonlinear dynamic behaviour ought to have more prominence in the discussion of the forecasting capabilities in climate prediction.

The thesis sets out to examine the utility of remote sensing techniques in helping to define recommendation domains relatively homogeneous agricultural areas - to act as foci for agricultural development planning in lower Meru, Kenya. Recommendation domains are used in farming systems research (FSR) for agricultural research and development initiatives enabling greater participation from rural producers within the development process. Recommendation domains are defined by agricultural potential (agro-ecological zones) and farming systems (agro-economic groupings). A multilevel approach incorporating Landsat MSS data, 1:50,000 stereo panchromatic air photography, large scale aerial colour slide photography and ground surveys is used to collect data on the farming systems of the study area. Relatively homogeneous farming patterns are identified and mapped using a number of different computer software packages. These patterns are related to previously identified zones of agricultural potential (agro-ecological zones) to define recommendation domains for new agricultural development initiatives in the area. Several domains are identified for specific attention. Recommendations are made which are relevant to both national and district level agricultural planning in Kenya. It is suggested that future development programmes should focus on areas undergoing population movement and cultivation change since without careful planning these changes are likely to detrimentally affect the local farming systems and natural environment.

This thesis proposes a construct to measure the competitiveness of Brazilian tourist destinations and orient the actions of public and private tourism managers. The model of this study is based on a relevant literature review, a panel with specialists that have expertise in Brazilian tourism and field research. The investigation was carried out in 15 Brazilian tourist cities, representative of the socioeconomic diversity that characterises the heterogeneity of a developing country. The results of the study show the level of competitiveness of these 15 destinations according to the 13 dimensions proposed in the model, identifying the strong and weak points of local tourism. An assessment was carried out in detail that should serve to assist public managers in the strategic planning of these cities now and in the future. As a complementary result, the study may be successfully replicated in other destinations, thus initiating a historical series for monitoring the competitiveness of Brazilian tourist destinations.

Urban morphology has been a longstanding field of interest for geographers but without adequate focus on its economic significance. From an economic perspective, urban morphology appears to be a fundamental determinant of house prices since morphology influences accessibility. This PhD thesis investigates the question of how the housing market values urban morphology. Specifically, it investigates people’s revealed preferences for street patterns. The research looks at two distinct types of housing market, one in the UK and the other in China, exploring both static and dynamic relationships between urban morphology and house price. A network analysis method known as space syntax is employed to quantify urban morphology features by computing systemic spatial accessibility indices from a model of a city’s street network. Three research questions are empirically tested. Firstly, does urban configuration influence property value, measured at either individual or aggregate (census output area) level, using the Cardiff housing market as a case study? The second empirical study investigates whether urban configurational features can be used to better delineate housing submarkets. Cardiff is again used as the case study. Thirdly, the research aims to find out how continuous change to the urban street network influences house price volatility at a micro-level. Data from Nanjing, China,is used to investigate this dynamic relationship. The results show that urban morphology does, in fact, have a statistically significant impact on housing price in these two distinctly different housing markets. I find that urban network morphology features can have both positive and negative impacts on housing price. By measuring different types of connectivity in a street network it is possible to identify which parts of the network are likely to have negative accessibility premiums (locations likely to be congested) and which parts are likely to have positive premiums (locations highly connected to destination opportunities). In the China case study, I find that this relationship holds dynamically as well as statically, showing evidence that price change is correlated with some aspects of network change.

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