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This paper examines the impact that alternative state planning frameworks have on five dimensions of urban development: density, the spatial extent of urbanised land area, property value, public expenditures on infrastructure and population change. The objectives of the analysis are threefold. First, the background discussion provides a brief overview of urban sprawl as a public policy problem and outlines how state growth management programmes attempt to respond to it. Secondly, the empirical analysis examines the effects of growth management in a cross-section of metropolitan counties during the 1982-97 time-period. The five outcome measures are modelled in a simultaneous equations framework in order to test several specific hypotheses about how state land-use policies affect the character of urban growth. Thirdly, the results of the empirical analysis are described within the context of previous research on the effectiveness of growth management. The findings suggest that state growth management programmes with strong consistency requirements and enforcement mechanisms hold much promise for reducing urban sprawl, while programmes that do not require consistency and/or have weak enforcement mechanisms may inadvertently contribute to it.

The current empirical analysis is set in the Seoul metropolitan area and attempted to analyze the Korean population's behavior vis-à-vis to open space and other factors that determine housing prices. Using the comprehensive real transaction price data and other geocoded socioeconomic data, the analysis reveals that marginal implicit prices can be monetized by using estimates from the revealed preference method of hedonic price analysis and shows the SMA residents are willing to pay higher premiums for green and open spaces and other favorable unit and location characteristics. For example, the present analysis shows that homes decrease in value at rates of 14,614 KRW and 9,958 KRW per meter of distance: homes located closer to these amenities are worth more than those located at a distance. It implies that the government needs to pay a great deal of attention in a location decision of green and open spaces since new investment in green and open spaces would be likely to entail positive externalities or pitfalls in general. The present analysis also suggests that, having marginal implicit prices in hand, a global demand curve can be derived - which can be then used as an important tool to estimate economic benefits of both environmental and non-environmental attributes of the project of our interests. It is important that economic benefits of environmental projects - public goods for which there is no entrance fee and therefore economic benefits cannot be estimated with a conventional economic analysis - can be estimated with revealed preference methods (i.e. hedonic price model) which are considered theoretically and empirically more sound than 2 Environmental Benefits of Green Space: Focusing on the Seoul Metropolitan Area stated preference methods such as contingent valuation method because revealed preference methods analyze the behavior of actual market participants with advanced statistical methods. Nevertheless, we should be cautious when applying hedonic price models to estimate economic benefits of environmental projects when the size and scale of the investment projects are large. This is because the scale and size of public goods investment projects that PIMAC analyzes are often so large that the spatially influenced area is also often large, which implies that it is likely that non-use values - which revealed preference methods cannot capture by nature - are in play. A vast size of area set in the present analysis helps to estimate economic benefits of large-scale projects. If non-use values are in play, however, socioeconomic benefits will be, in theory, smaller than benefits predicted by contingent valuation methods. In such cases, we need to be cautious for applying revealed preference methods. Nevertheless, contingent valuation methods are subject to various types of biases arisen from diverse sources inherent in surveys and the well-known fact that free riders consuming public goods are less likely to state their WTP accurately. This often entails political conflicts in an investment decision making, which gives lights to consideration of revealed preference methods such as hedonic price models given that a more robust structural model is developed by the research followed.

This paper addresses four fundamental questions about the relationship between `smart growth', a fiscally motivated anti-sprawl policy movement, and public finance. Do low-density, spatially extensive land use patterns cost more to support? If so, how large an influence does sprawl actually have? How does the influence differ among types of spending? And, how does it compare with the influence of other relevant factors? The analysis, which is based on the entire continental US and uses a series of spatial econometric models to evaluate one aggregate (total direct) and nine disaggregate (education, fire protection, housing and community development, libraries, parks and recreation, police protection, roadways, sewerage, and solid waste disposal) measures of spending, provides the most detailed evidence to date of how sprawl affects the vast sum of revenue that local governments spend every year.

ABSTRACT  Economic and demographic restructuring, along with the increasing desirability of environmental amenities, have driven growth in the eight‐state region of the Rocky Mountain West to extraordinary levels in recent decades. While social scientists have developed a solid conceptual understanding of the processes driving growth and change in the region, the broad nature of the land use outcomes associated with in‐migration has not received nearly as much scholarly attention. This article initiates an in‐depth empirical investigation on the magnitude, nature, and spatial variation of land use change in the Rocky Mountain West over the 1982‐1997 time period. Data from the USDA's National Resources Inventory reveals that the conversion of landscapes from rural to urban types of land uses varies significantly from place to place, not only in terms of total land developed, but also with respect to how population pressures and a number of other local characteristics of counties manifest themselves in the spatial pattern of growth.

Recent years have witnessed widespread expansion of state and regional planning programs in the United States. A major purpose of these efforts is to reduce urban sprawl—low density, discontinuous, suburban–style development, often characterized as the result of rapid, unplanned, and/or uncoordinated growth— by promoting jurisdictional cooperation and regulatory consistency across metropolitan areas. This paper evaluates the efficacy of this approach by examining the relationship between governmental fragmentation and several measurable outcomes of urban development: density, urbanized land area, property value, and public expenditures on infrastructure. The four dimensions are modeled in a simultaneous equations framework, providing substantive evidence on how fragmentation and other exogenous factors affect metropolitan growth patterns. Fragmentation is associated with lower densities and higher property values, but has no direct effect on public service expenditures; less fragmented metropolitan areas occupy greater amounts of land due to the extensive annexation needed to bring new development under the control of a central municipality. The findings of the analysis lend support to state and regional planning efforts aimed at increasing cooperation among local governments, but also suggest that further research is needed in order to evaluate whether or not they produce their intended effects.

AbstractThis paper presents a case study of the Donbas region, located in eastern Ukraine, focusing on efforts to de‐peripheralize the region prior to and after the outbreak of violence that engulfed it with the Russian invasion in early 2022. It sets out to use the lens of regional science and its sibling field, peace science, to impose some structure for understanding the still ongoing war. It does this by developing an economic history of the Donbas and a conceptual model for thinking about conflict and conflict resolution there. The implications of the model are explored using data on public opinion from 2014, a time of great uncertainty in the region. The model is also used to consider various counterfactual scenarios, and ultimately, to highlight the manner in which a peaceful solution escaped and the region's future was shattered by war. Overall, the paper represents an attempt to use the perspective of regional science to understand a complex and shifting conflict in real time. The project was undertaken with the aspiration that, by adding to knowledge on the Donbas and helping to disseminate awareness of its situation, it may contribute to the eventual recovery of Ukraine and its people.