Abstract
This chapter reviews developments associated with globalization—among them, dramatic changes in patterns of trade and the location of economic activities—and how these developments have affected the environmental footprints of cities and states or regions in which cities are located. It also discusses ways in which urban environmental footprints can be lightened. A critical part of any successful program with such an objective involves providing new and maintaining existing urban infrastructure systems that deliver food, energy, and water to cities and facilitate interurban—hence interregional and international—trade. The chapter thus concludes with a discussion of how one might provide analytical support for managing changes in urban infrastructure systems to lighten environmental footprints of cities, their hinterlands, and more distant settlements with which they trade.
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Computable General Equilibrium (CGE) modeling is an approach to applied economic analysis in which theories of economy-wide market behavior are used to impose structure in numerical thought experiments concerning matters of trade and development—and related policies—where the relative unavailability of data or the complexity of a theoretical model’s specification poses problems for a more traditional analytical or econometric modeling approach. Over the past thirty years, CGE modeling has developed extensively and has become a stock in trade of regional economists in particular. More recently, CGE models have taken on an explicit spatial orientation as the focus of modeling exercises has turned to analysis of location-specific impacts of unplanned events and planned industrial, infrastructural, environmental, or other types of regional policies. Spatial CGE models have been employed by researchers at various scales of spatial and temporal resolution to examine a wide variety of phenomena. Owing to the paucity of spatial time series, spatial CGE models provide logical frameworks within which a broad spectrum of spatial economic issues may be analyzed. See Donaghy (2009b) for a fuller discussion. There are a number of problems associated with the solution of such models. First is its sheer size: such models could easily have thousands of equations. While such a dimension is not uncommon for CGE models, the models would also have path variables and unavoidable non-convexities due to the coupling of various network layers. Consequently, nontraditional numerical solutions methods must be explored, include variational inequality methods, simulated annealing, genetic algorithms, and agent-based modeling methods. (See Friesz et al. (2007) and Zhang et al. (2005).)
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Donaghy, K., Beheshtian, A., Zhang, Z., Brown-Steiner, B. (2021). Environmental Impacts of Globalization. In: The Co-evolution of Commodity Flows, Economic Geography, and Emissions. Advances in Spatial Science. Springer, Cham. https://doi.org/10.1007/978-3-030-78555-0_2
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