Essays in applied microeconomics : job mobility and social networks

Nimczik, Jan Sebastian

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URN: urn:nbn:de:bsz:180-madoc-429717
Document Type: Doctoral dissertation
Year of publication: 2017
Place of publication: Mannheim
University: Universität Mannheim
Evaluator: Weber, Andrea
Date of oral examination: 12 October 2017
Publication language: English
Institution: Außerfakultäre Einrichtungen > Graduate School of Economic and Social Sciences - CDSE (Economics)
School of Law and Economics > VWL, Angewandte Politische Ökonomie (Weber, A. 2010-2016)
Subject: 330 Economics
Subject headings (SWD): Arbeitsmarkt , Einkommenssteuer
Keywords (English): Job Mobility , Social Networks , Labor Markets , Information Frictions
Abstract: In this thesis, I analyze the drivers and consequences, impediments and boundaries of job mobility with a particular focus on the role of network structures. My dissertation aims to help understanding the impact of social interactions between firms and workers on economic outcomes and decisions such as job mobility. In the first chapter, I exploit observed worker transitions in order to identify the boundaries of job mobility and, hence, the boundaries of labor markets. I propose a novel network-based method that allows to determine separate and largely selfcontained labor markets. In the second chapter, I examine how firm-level practices in taxation influence the behavior of individuals. In this context, worker flows between firms serve as a mechanism of information transmission and reduce information frictions. Informational uncertainties are also at the heart of the third chapter. In the context of hiring relations between firms, I show how learning processes through repeated interaction between firms can help to mitigate uncertainty about worker quality and, hence, lead to increased labor market efficiency. In the fourth chapter, I contribute to the range of econometric methods that deal with dependency structures in the data. I adjust the standard scheme for drawing cluster bootstrap resamples in order to accommodate the specific dependence structure in the data.

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