Essays in the analysis of matched employer-employee data

Haller, Jasper

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URN:	urn:nbn:de:bsz:180-madoc-633963
Dokumenttyp:	Dissertation
Erscheinungsjahr:	2022
Ort der Veröffentlichung:	Mannheim
Hochschule:	Universität Mannheim
Gutachter:	Weber, Andrea
Datum der mündl. Prüfung:	18 Oktober 2022
Sprache der Veröffentlichung:	Englisch
Einrichtung:	Außerfakultäre Einrichtungen > GESS - CDSE (VWL)
Lizenz:	Creative Commons Namensnennung 4.0 International (CC BY 4.0)
Fachgebiet:	330 Wirtschaft
Freie Schlagwörter (Englisch):	wage growth , job mobility , matched employer-employee data , discrimination , apprenticeship training
Abstract:	Traditionally, research in labor economics concerned itself with the study of workers or, less frequently, firms, but not both at the same time. While this research produced many classic results, it was necessarily silent on a host of important questions. Is there associative matching between high-wage workers and high-paying firms? To what extent are changes in worker outcomes attributable to sorting into different types of firms by unobservable characteristics? Conversely, to what extent are differences between firms, such as inter-industry wage gaps, attributable to sorting of different types of workers? How much, and through which channels, does the selection into high- or low-wage jobs contribute to wage growth? Do men obtain a higher share of firm-specific rents than women? These and many other important issues remained underexplored. It was the advent of large administrative datasets containing matched employer-employee data that opened a new segment within labor economics to tackle these issues. The seminal paper of Abowd, Kramarz, and Margolis (1999) set out a statistical framework for the analysis of matched employer-employee data and, perhaps even more importantly, staked out the substantive economic questions on which the analysis of employer-employee data would prove fruitful. More than twenty years later, countless contributions from across labor economics have harnessed matched employer-employee data to progress important economic issues. This dissertation situates itself in this tradition, and while it contains three quite distinct chapters, each with a different focus, the common thread is asking what we can learn by exploiting the observed mobility of workers across workplaces.