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Spatial econometric methods deal with the incorporation of spatial interaction and spatial structure into regression analysis. The field has seen a recent and rapid growth spurred both by theoretical concerns as well as by the need to be able to apply econometric models to emerging large geocoded data bases. The review presented in this chapter outlines the basic terminology and discusses in some detail the specification of spatial effects, estimation of spatial regression models, and specification tests for spatial effects.

This paper reviews a number of conceptual issues pertaining to the implementation of an explicit “spatial ” perspective in applied econometrics. It provides an overview of the motivation for including spatial effects in regression models, both from a theory-driven as well as from a data-driven perspective. Considerable attention is paid to the inferential framework necessary to carry out estimation and testing and the different assumptions, constraints and implications embedded in the various specifications available in the literature. The review combines insights from the traditional spatial econometrics literature as well as from geostatistics, biostatistics and medical image analysis.

This paper tests whether OECD countries compete with each other over corporate taxes in order to attract investment. We develop two models: with firm mobility, countries compete only over the statutory tax rate or the effective average tax rate, while with capital mobility, countries compete only over the effective marginal tax rate. We estimate the parameters of reaction functions using data from 21 countries between 1983 and 1999. We find evidence that countries compete over all three measures, but particularly over the statutory tax rate and the effective average tax rate. This is consistent with a belief amongst governments that location choices by multinational firms are discrete. We also find evidence of concave reaction functions, consistent with the model outlined in the paper.

This article outlines the motivation for a spatial approach as a novel focus for cross-disciplinary interaction and research in the social and behavioral sciences. The authors review the emerging interest in space and place in the recent social science literature and develop a vision for a spatially integrated social science. This vision provides the conceptual basis for a program of six activities designed to promote a spatial perspective: learning resources, workshops, bestpractice examples, place-based search, software tools, and a virtual community. The six programs will be informed by advances in the methods, technologies, and principles underlying spatial information science. The analysis of space and place has become an increasingly pivotal component of social science research in the past two decades. In part, this can be attributed to the transformation of social space around the globe, accompanied by shifts of varying degrees of magnitude in social science conceptualizing and theorizing. One aspect of these changes is subsumed under the general notion of “space-time compres-This article is a revised and shortened version of a proposal to the U.S. National Science Foundation (NSF) titled “SPESS: A Center for Spatially Enabled Social Science, ” which resulted in a five-year

Abstract: Since 1976, more than thirty states have eliminated their ‘death ’ taxes and many others have reduced them. This unexplored case of interstate tax competition presents a unique opportunity to develop a new, more satisfying definition of ‘competitor ’ based on historical elderly migration patterns. Using data from 1967 onward, we outline the recent history of state ‘death ’ tax competition and present a spatial econometric analysis. Interstate tax competition is evident and grows stronger when using migrationbased definitions of ‘competitors. ’ The paper concludes with still more evidence of interstate tax competition – the recent movement by states to effectively revive their ‘death ’ taxes.

INTRODUCTION The analysis of space and place has become an increasingly pivotal component of social science research during the past two decades. In part this is attributable to the transformation of social space around the globe, accompanied by shifts of varying degrees of magnitude in social science conceptualizing and theorizing. One aspect of these changes is subsumed under the general notion of "space-time compression" and results largely from such revolutions in information and communication technology as the microchip, satellite television, and low-cost, high-volume transoceanic shipping and travel. Other rapid transformations result from huge shifts in populations across the globe in migrations of unparalleled scope and scale. Also of note are the changing political landscapes of the late 20 th Century with their kaleidoscope effects of expanded (e.g., the European Community) or contracted (e.g., former Soviet Union states) territorial boundaries. All o

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Opponents of school vouchers sometimes charge that vouchers would drive many public school students to private schools, stripping funding and talented students from the public schools. Proponents say this is exactly what is needed to provide extra competition for public schools. Flight to private schools may happen if parents think private schools are good substitutes for public schools. For goods with explicit market prices, economists estimate substitutability by specifying a demand curve and finding a cross-price elasticity, but the non-market nature of schooling has prevented this. The current study finds a way to estimate the demand for public schooling and calculate a cross-price elasticity by exploiting Rosen’s (1974) two-stage hedonic technique. It estimates the cross-price elasticity between public schooling and the price of private schooling to be 0.66: Americans view private schools as moderately strong substitutes for public schools. However, the flight to private schools is likely to be stronger in high-income school districts than in low-income school districts. The use of spatial statistics accounts for potential spillovers and omitted variable bias in the house price hedonics and the demand curve estimation.

p. cm. Includes bibliographical references.