Vector Calculus in Regional Development Analysis : Comparative Regional Analysis Using the Example of Poland

Kesra Nermend

ISBN 10: 3790825832 / ISBN 13: 9783790825831

Editore: Physica-Verlag HD, 2010

Riguardo questo articolo

nach der Bestellung gedruckt Neuware - Printed after ordering - Methods used for regional development analysis are employed mainly to make forecasts and comparisons. Forecasting models of various types (e.g. econometric models) are usually used for forecasting. Recently, vector-autoregressive models (VAR) have become popular. These models were proposed by Sims in 1980. On the contrary, taxonomic methods (that are in the center of attention as far as the present publication is concerned) are most often employed to make comparisons. Linear ordering methods, including standard methods, are the most popular among ta- nomic methods. They are based on different distance and similarity measures, which leads to the fact that they do not always provide reliable information. When, for example, one construes the standard for a base year and then compares it with data for other years, it may turn out that the measure determined will have worse values than the standard for a real object (region, micro region) although this object is better from the standard. Hence, one must look for new methods employed in regional development analysis or improve hitherto existing ones in such a way so that information obtained re ects the reality to a larger extent. The main aim of the present publication is to work out methodological basis for regional development analysis based on vector calculus together with assumptions about computer system supporting the implementation of the method suggested.

Codice articolo 9783790825831

Dati bibliografici

• Titolo: Vector Calculus in Regional Development Analysis : Comparative Regional Analysis Using the Example of Poland
• Editore: Physica-Verlag HD
• Data di pubblicazione: 2010
• Lingua: Inglese
• ISBN 10: 3790825832
• ISBN 13: 9783790825831
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 235 L x 155 A x 11 P (millimetri) 235 millimetri di larghezza per 155 millimetri di altezza per 11 millimetri di profondità
• Peso: 289 grammi

Descrizione articolo

Riassunto

Methods used for regional development analysis are employed mainly to make forecasts and comparisons. Forecasting models of various types (e.g. econometric models) are usually used for forecasting. Recently, vector-autoregressive models (VAR) have become popular. These models were proposed by Sims in 1980. On the contrary, taxonomic methods (that are in the center of attention as far as the present publication is concerned) are most often employed to make comparisons. Linear ordering methods, including standard methods, are the most popular among ta- nomic methods. They are based on different distance and similarity measures, which leads to the fact that they do not always provide reliable information. When, for example, one construes the standard for a base year and then compares it with data for other years, it may turn out that the measure determined will have worse values than the standard for a real object (region, micro region) although this object is better from the standard. Hence, one must look for new methods employed in regional development analysis or improve hitherto existing ones in such a way so that information obtained re?ects the reality to a larger extent. The main aim of the present publication is to work out methodological basis for regional development analysis based on vector calculus together with assumptions about computer system supporting the implementation of the method suggested.

Dalla quarta di copertina

This work seeks to propose a methodological basis for regional development analysis based on vector calculus. Existing taxonomic methods are developed further in order to assess regions and micro-regions with regard to their socio-economic and environmental development. In addition to its methodological contribution, this book thus contributes to a framework of comparative assessment of regions and an analysis of underlying factors for regional development and investment decisions. In order to simplify the practical implementation of the presented concepts, the author proposes an IT application with the ability to examine spatial relations among groups of variables. The empirical research presented in this context relates to data from Polish counties as a case study.