Publikationsserver der Universitätsbibliothek Marburg
Titel:Patterns, Processes and Causes of Economic Growth
Autor:Duschl, Matthias
Weitere Beteiligte: Brenner, Thomas (Prof. Dr. Dr.)
Veröffentlicht:2015
URI:https://archiv.ub.uni-marburg.de/diss/z2015/0342
DOI: https://doi.org/10.17192/z2015.0342
URN: urn:nbn:de:hebis:04-z2015-03429
DDC: Wirtschaft
Titel (trans.):Muster, Prozesse und Ursachen des Wirtschaftswachstums
Publikationsdatum:2015-06-15
Lizenz:https://rightsstatements.org/vocab/InC-NC/1.0/

Dokument

Schlagwörter:
growth, Innovation, regions, Statistik, distribution, economic, Daten, Widerstandsfähigkeit ,, Schätzung, Wachstum, Simulation, firms, Cluster, Verteilung, Unternehmen, Wirtschaftswachstum, Economics, Region, Extremereignisse

Summary:
This thesis studies the patterns, processes and causes of economic growth at the level of firms and regions. How are growth rates of regional economies distributed and how do these distributions emerge? What are the implications of firm growth processes on the dynamics of regional economies? Which factors external to the firm, but internal to the region drive firm growth and what is the spatial dimension of their growth effects? And how are these factors causally related to each other at the regional level? In seven research papers, these questions are investigated on basis of comprehensive empirical data and innovative statistical approaches, taking especially into account the heterogeneity of firms, industries and space. A research gap on the stochastic characteristics of growth rates at the intermediate level between firms and countries is filled by fitting the Asymmetric Exponential Power (AEP) distribution to regional industry-specific employment data for Germany. Exploiting this additional information residing in the non-normality of the growth rates, the causal structure of economic, research, innovation and educational activities is uncovered within a structural vector autoregression framework, drawing on a unique industry-specific and multi-dimensional regional panel dataset. Introducing a conditional estimation approach of the AEP distribution in the context of the analysis of Chinese firm data, advantages from both ordinary regression and distributional approaches are combined. The role of firm dynamics for the aggregate economy is investigates by means of an empirically validated simulation models and conceptual work, in which firm dynamics assume a central role in the empirical implementation of the evolutionary perspective of regional resilience. Finally, geocoded micro-data, travel times and a flexible distance decay function approach provide more robust findings on the spatial extent of industrial clusters, unaffected from the Modifiable Areal Unit Problem, ultimately allowing for a more realistic assessment of the heterogeneous and firm-specific impacts of different kinds of agglomerations. The results of this thesis prove empirically the importance of taking into account the firm level dynamics and the heterogeneity across industries and space for the analysis of regional economic growth. Especially the frequency of extreme growth events, both at the level of firms and regions, and their role for regional development stand out. Besides, knowledge-generating activities are an important factor for growth, although their effects strongly depend on the industry and properties of the firm. Industrial clusters, which can take quite different spatial extensions, are not necessarily beneficial for the incumbent firms populating such a cluster. Finally, many stylized facts on the statistical properties of economic growth rates found in the literature survive at different aggregation levels, like regional economies, and national contexts, like in China.

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