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.     

Negative externalities on property values resulting from water impairment: The case of the Pigeon River Watershed

The objective of this research was to determine whether willingness to bear the negative externality from water quality impairment differs between those who do and those who do not receive economic benefit from the impairment source. Differences were tested using a hedonic analysis of ambient water quality in two discrete housing markets in the Pigeon River Watershed, which have been polluted by the operation of a paper mill. The results suggest that North Carolina residents residing in subwatersheds with impaired portions of the Pigeon River, who experience economic benefit from the paper mill in addition to its harmful effects on water quality, do perceive the pollution as a negative externality. In contrast, the effects of both the degraded river and its contributing streams on property values are perceived as negative externalities by watershed residents in Tennessee who experience only harmful effects from the pollution. Differences in willingness to bear the water-impairment externality were not indicated by variables representing view of and proximity to impaired water bodies. The results suggest that the perception of water quality to which property owners implicitly apply value should be considered when establishing water-quality regulations.     

The value of nonindigenous species risk assessment in international trade

Managing the introduction of nonindigenous species is becoming a major goal of policy-makers at regional, national and international scales. Here we investigate, at the national level, the ideal design and expected net benefits of a risk assessment program for evaluating the desirability of nonindigenous species imports. We show how to enhance the statistical rigor of such a system by correcting a common non-random sampling problem encountered in the data. This correction enables model output to be interpreted in an economically relevant way and facilitates a theoretically rigorous characterization of the balance between trade and nonindigenous species establishment risk. Using reptiles and amphibians imported to the U.S. as a case study, we characterize economic outcomes over a range of cases and demonstrate substantial expected returns to such a screening program, relative to the current effectively open-door policy. Our results are informative for the current debate in the U.S. about whether to require federal agencies to apply risk assessment before allowing a species for import. The framework presented decomposes a complex argument about risk management into component economic and statistical parts, allowing for debate and improved understanding over each element to inform the overall program in a transparent fashion.     

皖江城市带城市经济联系与中心城市辐射范围分析

分析经济区内城市间经济联系不仅有利于引导城市的空间发展,而且有利于空间经济的合理组织。以皖江城市带为例,引入克鲁格曼指数、建成区面积、人口素质权重系数等指标修正了以往的引力模型,并利用城市间的日发车班次数据对修正模型进行了检验。在此基础上,利用修正模型确定了各城市的主要对外联系方向及联系强度,采用断裂点公式计算了中心城市的吸引范围。结果表明:①皖江城市带内各城市对外经济联系强度差异较大;②各城市的主要联系方向呈现中心城市指向性和地域相邻指向性特征;③合肥和芜湖为皖江城市带的两个经济中心城市,它们的对外吸引范围较为狭小。     

家庭直接能耗的碳排放影响因素研究进展

家庭能源消费对环境的影响已经成为可持续发展领域热点研究课题之一。为了更好地开展家庭直接能耗的碳排放研究,对国际上近20年的研究进行总结分析,将国际上对家庭直接能耗碳排放影响因素的研究模型归纳为自上而下模型、自下而上模型及综合模型三大类,并对各种模型进行了评价;国际上对家庭直接能耗碳排放影响因素的研究集中于家庭外部环境、家庭特征及家庭成员3个方面。分析表明:家庭直接能耗碳排放影响因素的研究模型由简单走向综合;所用数据由历史统计数据到与微观住户调研数据相结合;研究的层面由国家(地区)、城市、社区向家庭内部全面展开;分析的视角由单一的宏观分析,到宏观与微观分析相结合。在基本反映家庭直接能耗碳排放影响因素研究的最新态势的同时,提出了我国家庭直接能耗碳排放影响因素研究中值得注意的几个问题。     

基于引力模型与0-1规划模型的省域经济区划——以江苏省为例

借助2008年统计数据,采用主成分法得到江苏各地级城市综合质量指数值;根据运输的时间成本与货币成本,计算江苏地级城市间经济距离;运用引力修正模型计算江苏地级城市间相互引力,并结合0-1规划模型划分经济区;依据经济区内县域间三次产业结构差异度与位置邻近性,划分经济亚区。研究表明：①江苏省可分为宁镇扬泰、苏锡常通、徐连宿、淮盐等4大经济区和15个经济亚区。②各城市连接的地区个数遵循Zipf定律,作为一、二级节点的南京和苏州统领全省经济空间网络,而南通、宿迁、盐城没有显著的联系对象。③江苏经济区空间分布逐渐由南北向格局转为南部呈东西向、北部呈南北向的格局。④各经济区内城市间的引力相差悬殊,南部较大,北部较小。省域尺度的经济区划,可为我国将来划分标准经济区奠定基础,也可为优化全省劳动地域分工格局提供依据。     

Technology level evaluation methodology based on the technology growth curve

Technology has been the driving force of development for knowledge-based economies. As competition in technology innovation among nations becomes more intense, there is a growing need for improved judgment, evaluation and prediction of scientific technology capacity in order to enhance national competitiveness. Until now, a country's technology level has been evaluated on a relative basis by comparing it with that of the country with the world's best technology. However, this kind of static methodology makes the interpretation of results unclear and makes time series analysis difficult. One of the most important limitations of this methodology is that it cannot be used to establish a strategy to improve the technology level. This paper examines the methodological problems of technology level evaluation and develops a dynamic methodology by applying the technology growth curve model. We also analyze the real technology level by using a new model application and review the relevance of this method. Finally, we discuss how to use the results in order to create a dynamic technology strategy.     

Where have all the flowers gone? Forecasting green trends in the automobile industry with a choice-based conjoint adoption model

With rising gas prices, global warming, and green thinking, all-electric vehicles are currently considered the automobile technology of the future. However, besides their advantages electric drive trains also exhibit several disadvantages. Moreover, history shows several failed attempts to establish electric vehicles. Thus, a reliable forecasting model is needed that predicts if the current trend is sustainable. We develop and empirically test a choice-based conjoint adoption model that uses individual-level preferences as a basis for prediction. Predictions are mapped to the time of the next planned purchase in order to establish the adoption process. The model extends existing research in several ways. First, no prior information, e.g., historical market data or a functional form of the adoption process, has to be integrated. Second, the model allows dynamic modifications of product specifications or competition at different points in time. Third, a no-choice option can be integrated so that a technology switch is not forced by the model itself and switching costs can be considered. The empirical results reveal different critical factors for the adoption of all-electric vehicles, such as purchase price, range, timing of the market entry, or environmental evolution, which could lead to a solid base of consumers preferring this option.