The house price determination process: Rational expectations with a spatial context

Applying the rational expectations hypothesis, this essay models the current value of a house as the conditional expectation of the discounted stream of housing services accruing to the owner of the house. The value of housing services is determined by neighborhood effects as well as the physical attributes of the property itself. In the existing hedonic literature, future transactions have not been utilized to describe neighborhood effects. The rational expectations asset pricing model in this study accounts for expected future neighborhood effects as well as observed current neighborhood effects. The reduced form of the rational expectations model is a spatial autoregressive (SAR) model with two spatial lags. After employing the generalized method of moments (GMM) in estimating the spatial asset pricing model, I find that both expected future transactions and prior transactions in the neighborhood are significant. The inclusion of expected future transaction prices in the neighborhood takes into account the influence of expected changes in the community and factors these potential changes into the current house price. This is consistent with forward-looking households. The forward-looking model generates superior out-of-sample prediction performance relative to both the conventional hedonic model without considering neighborhood effects or the standard spatial hedonic model including only past transactions.     

Who votes for public environmental goods in California?: Evidence from a spatial analysis of voting for environmental ballot measures

Voting referenda provide direct evidence of the demand for public goods. A number of previous studies have used referenda to analyze the support for public environmental goods. These studies have used aggregate data from large jurisdictional units (usually counties) and summary income measures such as the mean or median, and have usually found that higher income areas offer greater support for environmental propositions. We examine environmental referenda voting in California using census block group data, spatial dependence controls, and detailed income distribution data. We find that household income has a negative marginal effect on environmental referenda voting for most of the income range when using census block data. In addition, controls for spatial dependence significantly reduce the magnitude of most coefficients. This suggests that OLS estimates of referenda determinants are biased. We also show that county level data may be subject to severe aggregation bias and might not be appropriate for referenda studies.     

Using spatial microsimulation to account for demographic and spatial factors in environmental benefit transfer

This paper presents a simulation-based modelling approach for estimating total visitor numbers and amenity values for prospective non-priced open-access outdoor recreation sites. To begin, the geographic extent of the market for recreation at a policy site is estimated using data from a similar study site. The population residing within this geographic area is simulated using a spatial microsimulation model and GIS techniques and an individual-level ‘visitor arrival function’ is then transferred across this simulated population. This allows the latent demand for visits to the policy site by each simulated individual to be predicted and summed, providing an estimate of the total potential demand for recreation at the site. Combining this with an economic value measure of a visit provides an estimate of the potential amenity value of the policy site. The approach is applied to Moyode Wood, a small-scale forest in the West of Ireland, and estimates the potential total economic value of recreation at €0.4 million for the site. The research represents the first time that spatial microsimulation has been used in environmental benefit transfer and shows how it can be used to control for differences in demographic and spatial factors between study and policy sites. It also demonstrates how individual-level single-site travel cost models estimated using on-site survey data can be used to predict demand at alternative policy sites.     

Accounting for the ecosystem services of migratory species: Quantifying migration support and spatial subsidies

Migratory species support ecosystem process and function in multiple areas, establishing ecological linkages between their different habitats. As they travel, migratory species also provide ecosystem services to people in many different locations. Previous research suggests there may be spatial mismatches between locations where humans use services and the ecosystems that produce them. This occurs with migratory species, between the areas that most support the species' population viability - and hence their long-term ability to provide services - and the locations where species provide the most ecosystem services. This paper presents a conceptual framework for estimating how much a particular location supports the provision of ecosystem services in other locations, and for estimating the extent to which local benefits are dependent upon other locations. We also describe a method for estimating the net payment, or subsidy, owed by or to a location that balances benefits received and support provided by locations throughout the migratory range of multiple species. The ability to quantify these spatial subsidies could provide a foundation for the establishment of markets that incentivize cross-jurisdictional cooperative management of migratory species. It could also provide a mechanism for resolving conflicts over the sustainable and equitable allocation of exploited migratory species.     

区域技术创新及其影响因素的空间计量分析

利用空间统计的Moran指数和空间截面数据模型,对影响我国区域技术创新的因素进行计量分析。结果表明：区域创新环境对我国区域技术创新为显著的负效应;大学和创新企业对我国区域技术创新有显著的促进作用;研究机构对我国区域技术创新没有显著的贡献;创新企业对提高技术创新能力的贡献最大。     

连锁品牌空间定位模型及经济分析

本文通过建立引入连锁品牌空间定位系数、价格、选择成本的需求函数,并以此模型解释了连锁品牌空间定位的决策是通过空间定位系数和品牌信用度共同作用而实现的。同时对连锁品牌空间定位问题分为同一连锁品牌不同商圈、同一连锁品牌同一商圈、不同连锁品牌同一商圈这三种情况进行了解释分析,并对一些现实进行了论证。在理论分析的基础上,本文提出了连锁品牌空间定位的空间定位系数—品牌信用度二维模型,并分别从选择高空间定位系数商圈和提高品牌信用度建设方面为现实中的连锁品牌提供了相应的策略。     

Accommodating spatial correlation across choice alternatives in discrete choice models: an application to modeling residential location choice behavior

This paper presents a modeling methodology capable of accounting for spatial correlation across choice alternatives in discrete choice modeling applications. Many location choice (e.g., residential location, workplace location, destination location) modeling contexts involve choice sets where alternatives are spatially correlated with one another due to unobserved factors. In the presence of such spatial correlation, traditional discrete choice modeling methods that are often based on the assumption of independence among choice alternatives are not appropriate. In this paper, a Generalized Spatially Correlated Logit (GSCL) model that allows one to represent the degree of spatial correlation as a function of a multi-dimensional vector of attributes characterizing each pair of location choice alternatives is formulated and presented. The formulation of the GSCL model allows one to accommodate alternative correlation mechanisms rather than pre-imposing restrictive correlation assumptions on the location choice alternatives. The model is applied to the analysis of residential location choice behavior using a sample of households drawn from the 2000 San Francisco Bay Area Travel Survey (BATS) data set. Model estimation results obtained from the GSCL are compared against those obtained using the standard multinomial logit (MNL) model and the spatially correlated logit (SCL) model where only correlations across neighboring (or adjacent) alternatives are accommodated. Model findings suggest that there is significant spatial correlation across alternatives that do not share a common boundary, and that the GSCL offers the ability to more accurately capture spatial location choice behavior.     

A network-based analysis of the impact of structural damage on urban accessibility following a disaster: the case of the seismically damaged Port Au Prince and Carrefour urban road networks

The magnitude 7.0 earthquake that struck Haiti in January 2010 led to an unprecedented effort in collecting and providing geographical information in support of humanitarian aid. Although most of the compiled datasets and generated maps were able to provide specific and detailed information regarding the location of damaged buildings and road interruptions, none or little information was available to describe the accessibility—or otherwise—of the urban space. Here we try to offer an alternative method to define the urban accessibility landscape in the aftermath of earthquake damage, by combining simple graph theory concepts and GIS-based spatial analysis to assess how the urban space accessibility decreases when the road network is damaged.     

The evaluation of forest crop damages due to climate change. An application of Dempster–Shafer method

In order to assess damage risk caused by climate change in forest areas, Dempster–Shafer theory of evidence and fuzzy measures were applied to develop a framework for the estimation of economic forest damage. According to the definition of risk supported by the Intergovernmental Panel on Climate Change, a function of hazard and resilience lines of evidence was defined. The results of the hazard and resilience assessment were used to develop an economic framework based on Faustmann studies. The evaluation model, implemented through a spatial analysis procedure, was carried out linking Faustmann formula with hazard and resilience raster maps. The model permitted to estimate in monetary terms two possible costs to be supported: the first one is expressed as the expected damage to the forest crop on the basis of the current obtainable woody assortments and the second one referred to the potential expenses to pay in order to mitigate the risk. Finally, the framework was tested on an area of central Italy (Tuscany region).