Demographic trends depict a vibrant increase of the world population, particularly in Africa and Asia, and the share of people living in urban agglomerations is steeply growing when compared to rural areas. Increasing urban population and urban water demand often implies competition with other uses and users, notably the agricultural sector that accounts for the largest share of water diversions over the world. This thesis undertakes a critical analysis of the case of Hyderabad in the South-Indian state of Andhra Pradesh, one of India's fastest growing cities, to shed light on the process of administrative water allocation to cities from irrigated agriculture, an underdeveloped area of research. It does this by examining -1) the implications of Indian water institutional set-up on intersectoral water allocation; -2) Hyderabad water supply decision-making process, with focus on the role that politics have played; and -3) the impact of the urban water transfer on agriculture in general and on poor farmers more specifically, also reckoning on the contribution of groundwater in irrigated agriculture. The methodology adopted is based on the collection of primary and secondary data and encompasses-1 ) the analysis of water institutions in India and Andhra Pradesh; -2) an historical reconstruction of the main policy milestones of Hyderabad water supply and the study of intersectoral competition through a conflict analysis framework; -3) the calculation of surface water balances and groundwater withdrawals at one of Hyderabad water sources; and -4) the statistical analysis of primary data for determining the impact of shortages in canal water supply on poor farmers and their adaptive responses. A main research finding is that institutions vesting overarching powers over surface water on governments can expose urban water supply to harsh political opposition and chronic delays, in particular where farmers represent a large share of the electorate and transfers occur across regional boundaries. Then, this thesis demonstrates that intersectoral water transfers don't necessarily only bear negative effects on agriculture, notably if intersectoral water sharing rules are in place, and that groundwater may play a major role in compensating agriculture for urban water allocation. The research findings also show that poor farmers are those more likely to be negatively affected by water reallocations, not only because of reductions in canal water supply, but also because of social inequities in access to agricultural inputs in general and groundwater in particular.

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This thesis describes a combined exploratory analysis, on a fine spatial scale, of (i) England and Wales house prices, between the years 2000 and 2006; (ii) aggregate statistics taken from the UK census of 2001; and (iii) interaction statistics also taken from that census. The house price data is derived from individual transactions and analysed mainly in the form of ward level indices with a time resolution of 100 days. The study has twin aims: firstly, to improve understanding of the data set - which is large in nature - particularly with respect to exploring the interaction statistics; secondly, to improve the methods of exploratory analysis themselves. With respect to the aim of understanding the data, both migration and house price changes are visualised in a novel way, and regression is used to determine indicators of likely house price cross-correlations between different market areas. Ripple type effects are shown to be related both to reactive mechanisms, and to the composition of migration flows. Further visualisation shows that the market may be understood in terms of clusters with similar behaviour, or alternatively, in terms of market-driving and market-driven regions. Variables which can be used to define these clusters and regions are identified via further regression. With respect to improving the techniques of analysis, existing methods of visualising interaction data - based on clustering and linear ordering of points in geographic space - are extended to larger, hierarchical data sets and evaluated in this context. Novel approaches are presented for (i) construction of relative house price indices with minimal hedonic data, (ii) enhancement of time series predictions using cross-correlation data, and (iii) comparison of heterogeneous data sets via unification of all relevant information in the interaction domain, making it susceptible to analysis by regression aided with principal component based dimensionality reduction.

House prices have risen dramatically and it is evident that this has prevented many people from buying their own home, consequently increasing the demand for affordable housing within Ghana. Furthermore, demand for affordable housing across the country exceeds potential supply. Housing provided by the formal sector in the country is generally too expensive relative to income levels and the number of units built is insufficient. The formal sector caters mostly for upper income households where it is profitable for private developers to produce housing. Despite government efforts to provide social housing to attend the demands for housing of poor, only a fraction of the poor have been accommodated in this way. As a result, the housing problem in Ghana is the shortage of affordable accommodation for the urban poor; the low-income majority. In view of their inability to access housing through the formal channels, the poor take it upon themselves to build their own housing. Self- build housing or progressive housing has played a major role in the production of Ghanaian’s low-income housing stock. However, the ability of most households to build on their own is affected by many factors. The literature review found that the main constraints observed on the supply of this housing are access to titled land and access to construction finance. The land administration systems in Ghana can be described by two adjectives; complex and multiple. The entire systems have been governed by multiple laws, regulations, processes, standards and have been managed by multiple institutions with highly fragmented land administration structures, limited cooperation and coordination. As a result there are overlapping and duplication of functions and organisations and institutional management weaknesses are evident. This results in general indiscipline in the land market. There is a large number of mortgage financing institutions in Ghana, all of which have a mandate to provide credit facilities to the lower income groups at lower than market interest rates and long repayment periods. However, many self-builders households face series of problems in attempting to access finance with which to resolve their housing needs even though they have regular employment and income. To place the study in context, this volume aims to assess the impact of land tenure and administration systems on the provision of self-build housing by low income households with an argument that homeownership among low-income increases mostly through access to mortgage credits. Drawing on the insights from New Institutional Economies (NIE), the empirical analysis is undertaken in Kumasi, a major city of Ashanti Region, Ghana. The research is designed to triangulate data from a range of sources including questionnaires surveys, focus groups’ discussion and key informant interviews. The starting point is that there are significant problems surrounding affordability and accessibility to home ownership within the housing market. The research considers to what extent the lack of accessibility/affordability is determined simply by low incomes or access to credit or both. To address this problem the research focuses on the experience of key workers with low but regular verifiable incomes. The study showed that lending to self-builder households generally involves greater risks for lenders, and banks do not like to lend to these developers resulting in financial exclusion among the majority of households. At the same time the study found that the verification of incomes of loan applicants is insufficient and legal security of land tenure is a necessary prerequisite for the sanction of loans. The findings show that majority of the households lack formal title to their lands and building permission certificates to their properties. Further analysis suggested that this is a reflection of costly and lengthy administrative red tape of land institutions and agencies that is associated with acquiring land, developing land, registering and transferring titles and obtaining construction permits. In effect, the findings suggest that majority of households face financial exclusion. This has meant that many aspirations to homeownership have remained unfulfilled.

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This thesis presents three essays on analyst target prices. The essays contribute to the major debate on the value of analyst target prices in the capital market by addressing the following three questions: Does a bull-bear valuation analysis increase the accuracy of analysts’ target prices? Does analyst ranking affect how informative target prices are to institutional investors? And, do analysts use their cash flow forecasts when setting target prices?In the first essay, I explore whether conducting a bull–bear analysis (BBA) increases target price accuracy. A bull–bear analysis is a risk assessment tool that analysts use to enhance the credibility of their valuations and limit target price uncertainty. Using propensity score matching to control for selection bias, combined with a difference-in-differences estimation to allow for company- and analyst-specific effects, I estimate the effect of supplementing target prices with a BBA on the target price accuracy of US stocks during 2008–2009. The results suggest that target prices are more accurate when analysts supplement them with a BBA. The findings contribute to the literature exploring the determinants of analyst ability to produce accurate target prices. The second essay examines whether analyst ranking status affects institutional investors’ decisions to incorporate target price information into their investment strategies. Evidence shows that market participants value analyst target prices. There is limited evidence, however, on how target price revisions influence the decisions of sophisticated investors. The examination of this study is relevant for the economic question: Does analyst reputation mitigate or exacerbate the conflicts of interest that analysts face? Consistent with institutional investor trades being based on superior information, I observe differences in the information content of target price revisions by star and non-star analysts. Additionally, a duration analysis shows that the quality of analyst target price revisions significantly increases the hazard of analysts losing their star ranking.In the final essay, I examine whether analysts’ decisions to issue cash flow forecasts depend endogenously on their decision to use these forecasts to set target prices. Using an endogenous switching regression model, with analyst report regimes of disclosure and non-disclosure of cash flow forecasts, I find that cash flow revisions are more important than earnings revisions in explaining the magnitude of target price revisions in the cash flow disclosure regime. Cash flow forecasts influence and are influenced by analyst valuation choices. Additional analysis shows that cash flow-based pseudo-target prices play a greater role in explaining target price implied returns than do earnings-based pseudo-target prices. These findings provide insights into analysts’ valuation decision processes and their sophisticated valuation input choices.

In 1962, Reginald Ashley, the Secretary of the Scottish Allotments and Gardens Society, wrote that allotments are ‘the heritage of the tenement dweller’. He was writing at a time of great upheaval in the allotments movement; allotments had come under threat from post-war development and had largely lost their role in food production that had been vital during the Depression and both World Wars. In writing this statement, Ashley connected allotments to the idiosyncratic dwellings of Scottish city life; he made it clear that allotments are a part of, rather than an escape from, Scottish cities. For the Scottish Allotments and Gardens Society, allotments are not only there to grow food but they also improve the mental and physical health of tenement dwellers by providing them with their own outside space. This thesis will explore the role of the allotment within the city, using Glasgow as the location of study. It will use archival research and oral history interviews to answer five core research questions: how has the purpose of an allotment changed and developed from 1930 to the present day; how has the allotment movement advocated for these changing purposes; what has been the role of allotments in sustainable food production; how have allotments developed as places of community; and, what do allotments mean to individual plotholders. Through answering these five questions, this thesis will argue that allotments have developed as places of both individuality and community, a paradox that is needed for the health and well-being of plotholders. It will conclude that allotments are an integral part of Scottish cities that need to be included in long-term urban planning, providing protected green spaces for plotholders, communities, plants and animals in otherwise changing and developing urban environments.

The past three decades have witnessed the rapid development of the Chinese housing market , which is considered as a barometer of and an extremely crucial component of the whole Chinese economic system. Although some important findings have been obtained by previous research, many conclusions have been controversial and a comprehensive understanding of the mechanism and behaviour of the Chinese housing system is a worthwhile endeavour. The existing studies about the Chinese housing market are mostly confined to qualitative analysis, lacking the support of a theoretical basis and empirical research. This thesis aims to employ more recent econometrical methodologies, from both theoretical and empirical perspectives, to systematically analyse several prevalent issues of the Chinese housing market. More specifically, this thesis is going to explore the main determinants of house prices, the convergence and ripple effects of regional house prices, and the interactive relationship between housing conditions and individual’s subjective well-being. Some empirical findings can be drawn from this thesis: 1) by using the system GMM dynamic panel data models, the results indicate that Chinese house prices are mainly affected by factors related to government policies and speculative demand rather than the urbanization process, which is understandable in a non-fully market-oriented status quo; 2) there is evidence of very limited convergence of regional house prices by employing unit root tests, σ-convergence and β-convergence approaches; however, the alternative methods, such as panel regression models, Engle-Granger/Johansen cointegration tests and Granger Causality tests, imply that house prices can ripple out from some core cities to other cities; 3) the results of the Ordered Probit Models suggest that the housing conditions in urban areas play a significant role in peoples’ subjective well-being in respect of housing satisfaction and overall happiness; additionally, the effects of housing factors impact on different groups of residents in different ways. Due to the limitations of data sources in the early days, this thesis is the first to combine such a wide panel data series, on both the time dimension and geographic dimension, to study the Chinese Housing Market. Also, when analysing the convergence and ripple effects models, this thesis transfers the original link indexes used by previous scholars into modified constant growth indexes, which improves the efficiency of empirical models to a greater extent. In addition, approaches using the system GMM method, σ- and β-convergence analysis, Engle-Granger/Johansen cointegration tests and Granger Causality tests are first introduced into the study of the Chinese housing market, generally achieving good results especially in the determinants of house prices and the ripple effects of regional house prices. Moreover, except for the commonly used method of the Ordered Probit Model for the questionnaire survey research, this thesis produces the predicted value of housing satisfaction by using two-stage estimations, to investigate the effects of housing conditions and housing satisfaction on people’s overall happiness. Meanwhile, the approach of ‘money equivalent effects’ is also a new perspective in detecting the effects of housing conditions on overall happiness.

In light of the financial and property crisis of 2007-2013 it is difficult to ignore the existence of cycles in the general business sector, as well as in building and property. Moreover, this issue has grown to have significant importance in the UK, as the UK property market has been characterized by boom and bust cycles with a negative impact on the overall UK economy. Hence, an understanding of property cycles can be a determinant of success for anyone working in the property industry. This thesis reviews chronological research on the subject, which stretches over a century, characterises the major publications and commentary on the subject, and discusses their major implications. Subsequently, this thesis investigates property forecasting accuracy and its improvement. As the research suggests, commercial property market modelling and forecasting has been the subject of a number of studies. As a result, it led to the development of various forecasting models ranging from simple Single Exponential Smoothing specifications to more complex Econometric with stationary data techniques. However, as the findings suggest, despite these advancements in commercial property cycle modelling and forecasting, there still remains a degree of inaccuracy between model outputs and actual property market performance. The research therefore presents the principle of Combination Forecasting as a technique helping to achieve greater predictive outcomes. The research subsequently assesses whether combination forecasts from different forecasting techniques are better than single model outputs. It examines which of them - combination or single forecast - fits the UK commercial property market better, and which of these options forecasts best. As the results of the study suggest, Combination Forecasting, and Regression (OLS) based Combination Forecasting in particular, is useful for improving forecasting accuracy of commercial property cycles in the UK.