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Roberta Capello and Peter Nijkamp

The space-economy has never been static, but has always shown a state of flux. Regions are normally in transition; they are work in progress. As a consequence, we observe a complex evolution of regional systems that varies between growth and decline. Static location and allocation theories may be helpful in understanding underlying structures in regional economies, but do not offer a full-scale picture of the development of multi-actor processes and of the perpetual or temporal impediments for regional growth and prosperity. The conceptualization and solid explanation of regional growth, and differences therein, is still largely a mystery for the research community in many countries. There is no uniform panacea for enhancing or accelerating the development trajectory of regions in a national or supranational economy. Therefore, regional policy is still in many cases a black box; the outcomes of intensified regional growth strategies are often largely unpredictable. Best guesses are more common than testable and operational estimates of policy impacts. Against the above-mentioned backgrounds, the editors of the Handbook of Regional Growth and Development Theories published a decade ago a comprehensive volume with a rich collection of advanced contributions on the above challenges in regional economics and regional science. In the ten years since then the world, both the empirical regional world and the theoretical and empirical reflection on growth and development issues, has not come to a standstill. We have become sadder and wiser after economic crises, regional fragmentation trends, the introduction of radical technological innovation, and the awareness of failures of regional policy. However, we have also enriched our knowledge horizon, with new insights and new methods and theories of regional analysis. The time has now come to take a refreshing and new look at the achievements of regional growth and development theories.

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Martin Jones

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Edited by John R. Bryson, Lauren Andres and Rachel Mulhall

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Åke E. Andersson and David Emanuel Andersson

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Åke E. Andersson and David Emanuel Andersson

The games of markets including entrepreneur-driven economic development have always taken place on an arena of the combined material and non-material infrastructure. The infrastructure thus constitutes the arena; it is public capital that facilitates and constrains the rapid “games” of buying and selling that economic agents play. Agents perceive the arena as stable because its evolution is so much slower than that of markets for goods and services. Synergetic theory is well equipped to handle such multiple timescales. Its application to economic phenomena enables us to show that competitive equilibrium theory requires prior specification of the infrastructural arena, which consists of public knowledge, space-bridging networks and institutions. Synergetic theory can also help us avoid the pitfalls of conventional macroeconomic theory. In this chapter, we demonstrate how macroeconomic equilibrium depends on the infrastructure. We claim that all goods are durable and are thus instances of capital. This means that historical trajectories, current outcomes, uncertain expectations and changes in spatial accessibility all influence the growth and fluctuations in the value of capital goods. Dynamic non-linear interactions between scientists, inventors and entrepreneurs affect investments. New technological or design ideas spread most easily among spatially proximate firms within communication and transport networks. Such network effects shape processes of spatial clustering, agglomeration and urbanization. Based on causal and various econometric considerations, it has been common for economists to resort to difference equation in their modeling strategies. But if we include dynamic interactions within a system of difference equations—so as to accommodate realistic causal assumptions—it will often result in complex models with chaotic outcomes. However, there are ways out of chaos in economic modeling. The first is to focus on continuous dynamic synergetic models, which implies a careful separation of variables and dynamic processes according to their relevant timescales as well as the collectiveness of their impacts.

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Jason Potts

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Philip McCann

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Edited by Peter Karl Kresl and Jaime Sobrino

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Allen J. Scott