Analyzes the major economic issues confronting less-developed countries.

This book provides the first comprehensive and critical examination of Mäki’s realist philosophy of economics.

This valuable book contributes substantively to the current state-of-the-art of macroeconomics. It provides a method for building models in which business cycles and economic growth emerge from the interactions of a large number of heterogeneous agents. Drawing from recent advances in agent-based computational modeling, the authors show how insights from dispersed fields can be fruitfully combined to improve our understanding of macroeconomic dynamics.

The articles collected in this volume have two features in common: they wantto integrate economics, demography and geography, and they want to overcome the stationary approach in modelling in favour of a dynamic one. The book is subdivided into three parts, where Part I is focussing on economic evolution, Part II on geographical development and Part III is related to demographic change. The present volume aims at providing a new look at this triangle in view of the classical background of discussions by introducing new research ideas focussing in nonlinear dynamics and stochastic modelling. Thus the main purpose of this book is to make a contribution to the interdisciplinary work needed to integrate the effortsbetween these three research fields and to serve as a research source in demonstrating the current state of art in dynamic modelling. The book isaddressed to social scientists in general, and those in particular with a background in economics, geographics and demographics. It should also be of interest to mathematicians, physicists, and systems analysts interested in model building and applications of nonlinear dynamics.

Growing inequalities in Europe are a major challenge threatening the sustainability of urban communities and the competiveness of European cities. While the levels of socio-economic segregation in European cities are still modest compared to some parts of the world, the poor are increasingly concentrating spatially within capital cities across Europe. An overlooked area of research, this book offers a systematic and representative account of the spatial dimension of rising inequalities in Europe. This book provides rigorous comparative evidence on socio-economic segregation from 13 European cities. Cities include Amsterdam, Athens, Budapest, London, Milan, Madrid, Oslo, Prague, Riga, Stockholm, Tallinn, Vienna and Vilnius. Comparing 2001 and 2011, this multi-factor approach links segregation to four underlying universal structural factors: social inequalities, global city status, welfare regimes and housing systems. Hypothetical segregation levels derived from those factors are compared to actual segregation levels in all cities. Each chapter provides an in-depth and context sensitive discussion of the unique features shaping inequalities and segregation in the case study cities. The main conclusion of the book is that the spatial gap between the poor and the rich is widening in capital cities across Europe, which threatens to harm the social stability of European cities. This book will be a key reference on increasing segregation and will provide valuable insights to students, researchers and policy makers who are interested in the spatial dimension of social inequality in European cities. Chapters 1 and 15 of this book are freely available as downloadable Open Access PDFs at http://www.taylorfrancis.com under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 3.0 license.

Our interest in problems of aggregation originates from about seven years ago when we became involved in research in the field of applied microeconomics. To our astonishment a vast majority of researchers in this area took it for granted that their, mostly thoroughly derived, micro models could meaningfully be confronted with per capita data. Nany of them did not even realize - at least they gave no utterance to it - that applying macro data in micro models raises considerable problems. Those who did mention the difficulty, almost always belittled its importance. Fortunately, there are noteworthy exceptions. Thinking about aggregation raises at least two questions: "Why or why not aggregate?" and "How to aggregate and, in particular, to what degree?" General answers to these questions can only be given in uninformative wording (as many assertions in economics): one aggregates for the sake of tractability, because of the lack of (individual) data, to avoid or to reduce multicollineartiy, to save degrees of freedom; one abstains from aggregation to avoid loss of information, to avoid aggregation biases and one aggregates such and to such degree as to bypass or reduce the drawbacks mentioned above.