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Spatial Knowledge Spillovers and the Dynamics of Agglomeration and Regional Growth [electronic resource] / by Max C. Keilbach.

By: Contributor(s): Material type: TextTextSeries: Contributions to EconomicsPublisher: Heidelberg : Physica-Verlag HD : Imprint: Physica, 2000Edition: 1st ed. 2000Description: X, 194 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783642576980
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 330.015195
LOC classification:
  • HB139-141
Online resources:
Contents:
1 Introduction and Motivation -- 2 Why and How Does Economic Activity Grow? An Overview of the Literature -- 3 Why and How Does Economic Activity Concentrate in Space? Another Overview of the Literature -- 4 Spatial Knowledge Spillovers and the Dynamics of Agglomeration and Regional Growth -- 5 Marshallian Externalities, Spatial Self-Organization and Regional Growth - an Agent Based Approach -- 6 Spatial Processes in the Economy - an Empirical Investigation -- 7 Summary and Conclusion -- A Generalization of the Model Developed in Chapter 4 -- A. 1 Illustration of the Allocation Dynamics for a Region with an Arbitrary Number of Firms -- A.2 Proof that Firms Employ Identical Factor Ratios or Identical Factor Shares -- B Mathematical Appendix -- B.l Proof that the Bias of an OLS Estimation in the Presence of Spatial Autocorrelation is Biased -- B.2 Derivation of the Log-Likelihood Function of Model (6.2) -- C Data -- List of Symbols -- List of Figures -- List of Tables -- References.
In: Springer Nature eBookSummary: When considering the dynamics of regional growth rates, one usually observes growth convergence on spatial aggregates but non-convergence or even divergence within smaller regions of different type. This book suggests various approaches to investigate this puzzle. A formal model, merging approaches from growth theory and new economic geography, shows that spatial knowledge spillovers might be the driving force behind this behavior. To analyze an arbitrary number of regions, the model is implemented on a locally recursive simulation tool - cellular automata. Convergence regressions from different runs of the automaton confirm previous findings. Finally, the existence of spatial knowledge spillovers is tested. Regressions give strong evidence for spatial knowledge spillovers. All the relevant literature and spatial econometric methods are surveyed. Data is reproduced in the appendix.
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E-Book E-Book Biblioteca Digital Colección SPRINGER 330.015195 (Browse shelf(Opens below)) Not For Loan
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1 Introduction and Motivation -- 2 Why and How Does Economic Activity Grow? An Overview of the Literature -- 3 Why and How Does Economic Activity Concentrate in Space? Another Overview of the Literature -- 4 Spatial Knowledge Spillovers and the Dynamics of Agglomeration and Regional Growth -- 5 Marshallian Externalities, Spatial Self-Organization and Regional Growth - an Agent Based Approach -- 6 Spatial Processes in the Economy - an Empirical Investigation -- 7 Summary and Conclusion -- A Generalization of the Model Developed in Chapter 4 -- A. 1 Illustration of the Allocation Dynamics for a Region with an Arbitrary Number of Firms -- A.2 Proof that Firms Employ Identical Factor Ratios or Identical Factor Shares -- B Mathematical Appendix -- B.l Proof that the Bias of an OLS Estimation in the Presence of Spatial Autocorrelation is Biased -- B.2 Derivation of the Log-Likelihood Function of Model (6.2) -- C Data -- List of Symbols -- List of Figures -- List of Tables -- References.

When considering the dynamics of regional growth rates, one usually observes growth convergence on spatial aggregates but non-convergence or even divergence within smaller regions of different type. This book suggests various approaches to investigate this puzzle. A formal model, merging approaches from growth theory and new economic geography, shows that spatial knowledge spillovers might be the driving force behind this behavior. To analyze an arbitrary number of regions, the model is implemented on a locally recursive simulation tool - cellular automata. Convergence regressions from different runs of the automaton confirm previous findings. Finally, the existence of spatial knowledge spillovers is tested. Regressions give strong evidence for spatial knowledge spillovers. All the relevant literature and spatial econometric methods are surveyed. Data is reproduced in the appendix.

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