Quantitative Methods in Regional Science: Perspectives on Research Directions

Abstract

The use of formal mathematical concepts and expressions, and the application of statistics, optimization and other quantitative methods constitutes the most common characteristic of research in regional science as it has become known over the past thirty years. To address the current state of the art and to outline potential future developments for quantitative methods in regional science would therefore be a rather formidable task. In order to focus the discussion, and to limit the overlap with the other papers in the series that address substantive research areas (e. g., spatial interaction and migration, location, regional development, energy and the environment), I will limit the scope of my remarks to two specific areas. I will focus on operational models of the urban and regional economy, and on methods for the analysis of spatial data. Both of these are areas in which recently some important new developments have come to the fore. In addition, these are also areas in which the quantitative methods have made the transition into the practice of planners and policy makers. Even though my choice of topic is admittedly narrow, it allows a focus on those methods that have emphasized and dealt with the central role of space in regional science models. Arguably, this is less the case with some other, and equally important sets of techniques, such as optimization methods and decision theory. In addition to these conceptual motivations, there is also a practical constraint on the length of the paper, which precluded me from covering a more comprehensive range of topics.