Mathematical Models in Regional Economics

This chapter reviews the evolution of mathematical and statistical models that have been used for the development of theory and policy analysis in regional economics. The benefits of mathematical approaches are outlined. Theories and estimation techniques have developed in tandem with developments in the availability of geo-referenced data, new technologies and particularly computing power. Regional modeling was initially strongly influenced by macro-econometric and input-output models developed for national economies, but evolved into models that integrated these approaches into multi-regional settings that are often of a highly nonlinear nature and explicitly account for various forms of spatial interaction. New theoretical developments such as the new economic geography and endogenous growth theory have had a major impact on recent modeling trends and on the increasing popularity of spatial econometrics. Regional economic modeling has a long tradition of integrating approaches from different disciplines and in this paper we provide several examples of trans-disciplinary advances, notably entropy-interpretations of spatial interaction, computational neural networks and complexity theory. We conclude with outlining a range of areas of regional modeling in which promising developments are likely.