Spatial housing economics: a survey

This introduction to the Virtual Special Issue surveys the development of spatial housing economics from its roots in neo-classical theory, through more recent developments in social interactions modelling, and touching on the role of institutions, path dependence and economic history. The survey also points to some of the more promising future directions for the subject that are beginning to appear in the literature. The survey covers elements hedonic models, spatial econometrics, neighbourhood models, housing market areas, housing supply, models of segregation, migration, housing tenure, sub-national house price modelling including the so-called ripple effect, and agent-based models. Possible future directions are set in the context of a selection of recent papers that have appeared in Urban Studies. Nevertheless, there are still important gaps in the literature that merit further attention, arising at least partly from emerging policy problems. These include more research on housing and biodiversity, the relationship between housing and civil unrest, the effects of changing age distributions - notably housing for the elderly - and the impact of different international institutional structures. Methodologically, developments in Big Data provide an exciting framework for future work.

A review of models of spatial innovation infrastructures in support of high growth SMEs

This Paper first provides a review and analysis of the recent trends on innovation infrastructures developed in industrialised countries to promote innovation and competitiveness for high growth SMEs. It specifically aims to examine various spatial models developed to support provision of innovation infrastructure for high growth sector.

Spatial information infrastructure : what can it possibly mean?

Investment begins with imagining that doing something new in the present will lead to a better future. Investment can vary from incidental improvements as safe and beneficial side-effects of current activity through to a more dedicated and riskier disinvestment in current methods of operation and reinvestment in new processes and products. The role of government has an underlying continuity determined by its constitution that authorises a parliament to legislate for peace, order and good government. ‘Good government’ is usually interpreted as improving the living standards of its citizens. The requirements for social order and social cohesion suggest that improvements should be shared fairly by all citizens through all of their lives. Arguably, the need to maintain an individual’s metabolism has a social counterpart in the ‘collective metabolism’ of a sustainable and productive society.

The influence of human rights on land rights and spatial information

This paper reviews the growing influence of human rights issues on land rights, administration, management and tenure. In the last few decades, attention focussed on integrating economic and environmental considerations to achieve sustainable land use. The World Trade Organisation began in 1995. As a condition of membership, nations undertook legislative programmes aimed at reducing price distortions and barriers to international trade. Reducing trade barriers has direct effects on agricultural production as a major land use. Similarly, as signatories to the 1992 Rio Declaration, nations undertook caring for and reporting on the state of the environment. However, quality of life is also an issue in deciding what is sustainable development. The Universal Declaration of Human Rights, proclaimed in 1948, provided a framework for a series of international human rights conventions. These conventions now influence national legislative programmes. The purpose of this paper is to review some of the implications of human rights on rights in land and the production and use of spatial information.

A new approach to spatial data interpolation using higher-order statistics

Interpolation techniques for spatial data have been applied frequently in various fields of geosciences. Although most conventional interpolation methods assume that it is sufficient to use first- and second-order statistics to characterize random fields, researchers have now realized that these methods cannot always provide reliable interpolation results, since geological and environmental phenomena tend to be very complex, presenting non-Gaussian distribution and/or non-linear inter-variable relationship. This paper proposes a new approach to the interpolation of spatial data, which can be applied with great flexibility. Suitable cross-variable higher-order spatial statistics are developed to measure the spatial relationship between the random variable at an unsampled location and those in its neighbourhood. Given the computed cross-variable higher-order spatial statistics, the conditional probability density function (CPDF) is approximated via polynomial expansions, which is then utilized to determine the interpolated value at the unsampled location as an expectation. In addition, the uncertainty associated with the interpolation is quantified by constructing prediction intervals of interpolated values. The proposed method is applied to a mineral deposit dataset, and the results demonstrate that it outperforms kriging methods in uncertainty quantification. The introduction of the cross-variable higher-order spatial statistics noticeably improves the quality of the interpolation since it enriches the information that can be extracted from the observed data, and this benefit is substantial when working with data that are sparse or have non-trivial dependence structures.

Model selection with misspecified spatial covariance structure

Spatial data analysis has become more and more important in the studies of ecology and economics during the last decade. One focus of spatial data analysis is how to select predictors, variance functions and correlation functions. However, in general, the true covariance function is unknown and the working covariance structure is often misspecified. In this paper, our target is to find a good strategy to identify the best model from the candidate set using model selection criteria. This paper is to evaluate the ability of some information criteria (corrected Akaike information criterion, Bayesian information criterion (BIC) and residual information criterion (RIC)) for choosing the optimal model when the working correlation function, the working variance function and the working mean function are correct or misspecified. Simulations are carried out for small to moderate sample sizes. Four candidate covariance functions (exponential, Gaussian, Matern and rational quadratic) are used in simulation studies. With the summary in simulation results, we find that the misspecified working correlation structure can still capture some spatial correlation information in model fitting. When the sample size is large enough, BIC and RIC perform well even if the the working covariance is misspecified. Moreover, the performance of these information criteria is related to the average level of model fitting which can be indicated by the average adjusted R square ( [GRAPHICS] ), and overall RIC performs well.

Internet based spatial data delivery and reporting system for cotton industry

Development of an internet based spatial data delivery and reporting system for the Australian Cotton Industry.

Sustainable grazing management for temporal and spatial variability in north Australian rangelands – a synthesis of the latest evidence and recommendations

Rainfall variability is a major challenge to sustainable grazing management in northern Australia, with management often complicated further by large, spatially-heterogeneous paddocks. This paper presents the latest grazing research and associated bio-economic modelling from northern Australia and assesses the extent to which current recommendations to manage for these issues are supported. Overall, stocking around the safe long-term carrying capacity will maintain land condition and maximise long-term profitability. However, stocking rates should be varied in a risk-averse manner as pasture availability varies between years. Periodic wet-season spelling is also essential to maintain pasture condition and allow recovery of overgrazed areas. Uneven grazing distributions can be partially managed through fencing, providing additional water-points and in some cases patch-burning, although the economics of infrastructure development are extremely context-dependent. Overall, complex multi-paddock grazing systems do not appear justified in northern Australia. Provided the key management principles outlined above are applied in an active, adaptive manner, acceptable economic and environmental outcomes will be achieved irrespective of the grazing system applied.

Topics in Spatial Econometrics - With Applications to House Prices

Topics in Spatial Econometrics — With Applications to House Prices Spatial effects in data occur when geographical closeness of observations influences the relation between the observations. When two points on a map are close to each other, the observed values on a variable at those points tend to be similar. The further away the two points are from each other, the less similar the observed values tend to be. Recent technical developments, geographical information systems (GIS) and global positioning systems (GPS) have brought about a renewed interest in spatial matters. For instance, it is possible to observe the exact location of an observation and combine it with other characteristics. Spatial econometrics integrates spatial aspects into econometric models and analysis. The thesis concentrates mainly on methodological issues, but the findings are illustrated by empirical studies on house price data. The thesis consists of an introductory chapter and four essays. The introductory chapter presents an overview of topics and problems in spatial econometrics. It discusses spatial effects, spatial weights matrices, especially k-nearest neighbours weights matrices, and various spatial econometric models, as well as estimation methods and inference. Further, the problem of omitted variables, a few computational and empirical aspects, the bootstrap procedure and the spatial J-test are presented. In addition, a discussion on hedonic house price models is included. In the first essay a comparison is made between spatial econometrics and time series analysis. By restricting the attention to unilateral spatial autoregressive processes, it is shown that a unilateral spatial autoregression, which enjoys similar properties as an autoregression with time series, can be defined. By an empirical study on house price data the second essay shows that it is possible to form coordinate-based, spatially autoregressive variables, which are at least to some extent able to replace the spatial structure in a spatial econometric model. In the third essay a strategy for specifying a k-nearest neighbours weights matrix by applying the spatial J-test is suggested, studied and demonstrated. In the final fourth essay the properties of the asymptotic spatial J-test are further examined. A simulation study shows that the spatial J-test can be used for distinguishing between general spatial models with different k-nearest neighbours weights matrices. A bootstrap spatial J-test is suggested to correct the size of the asymptotic test in small samples.

Spatial and temporal flows of China's forest resources: Development of a framework for evaluating resource efficiency

Science & Technology Basic Work Program of China: Scientific Survey of the Middle-lower Reaches of Lantsang River and the Great Shangri-La Region [2008FY110300]; National Basic Research Program of China (973 Program): Ecosystem Services and Ecological Safety of the Major Terrestrial Ecosystems of China [2009CB421106]; National Natural Science Foundation of China [30670374]; EU ; European Commission, DG Research [003874]

Valuing the health benefits of physical activities in the marine environment and their importance for marine spatial planning

The marine environment provides a number of services which contribute to human well-being including the provision of food, regulation of climate and the provision of settings for cultural gains. To ensure these services continue to be provided, effective management is required and is being strategically implemented through the development of marine spatial plans. These plans require an understanding of the costs and benefits associated with alternative marine uses and how they contribute to human well-being. One benefit which is often difficult to quantify is the health benefit of engaging with the marine environment. To address this, the research develops an approach which can estimate the contribution aquatic physical activities makes to quality adjusted life years (QALYs) in monetary and non-monetary terms. Using data from the Health Survey for England, the research estimates that physical activities undertaken in aquatic environments at a national level provides a total gain of 24,853 QALYs. A conservative estimate of the monetary value of a QALY gain of this magnitude is £176 million. This approach provides estimates of health benefits which can be used in more comprehensive impact assessments, such as cost-benefit analysis, to compare alternative marine spatial plans. The paper concludes by discussing future steps.

Valuing the health benefits of physical activities in the marine environment and their importance for marine spatial planning

The marine environment provides a number of services which contribute to human well-being including the provision of food, regulation of climate and the provision of settings for cultural gains. To ensure these services continue to be provided, effective management is required and is being strategically implemented through the development of marine spatial plans. These plans require an understanding of the costs and benefits associated with alternative marine uses and how they contribute to human well-being. One benefit which is often difficult to quantify is the health benefit of engaging with the marine environment. To address this, the research develops an approach which can estimate the contribution aquatic physical activities makes to quality adjusted life years (QALYs) in monetary and non-monetary terms. Using data from the Health Survey for England, the research estimates that physical activities undertaken in aquatic environments at a national level provides a total gain of 24,853 QALYs. A conservative estimate of the monetary value of a QALY gain of this magnitude is £176 million. This approach provides estimates of health benefits which can be used in more comprehensive impact assessments, such as cost-benefit analysis, to compare alternative marine spatial plans. The paper concludes by discussing future steps.