This dissertation contributes to the empirical literature on job quality. The first chapter introduces the broader debate and presents the overall structure of the thesis. The second chapter examines the implications of agglomeration for job quality using an urban–rural comparative approach across multiple indicators. The results show that rural workers are better off in terms of work intensity and job satisfaction, while urban workers benefit from stronger job-match opportunities. Overall, the findings support the view that adopting a job quality lens can usefully complement assessments of the welfare desirability of urbanization. The third chapter investigates the intrinsic value that workers derive from performing occupations that include tasks beneficial to the environment- so-called green jobs- using the concept of meaningful work. The analysis confirms that workers gain intrinsic value from green jobs, conditional on the broader social-norms/policy-context. The favourable labour supply responses associated with meaningful work suggest that workers should be considered a key lever for achieving the green transition. The fourth chapter analyses how poor evaluations of job attributes predict labour turnover, highlighting the particular role of intangible job attributes, measured through indicators such as interesting work, learning opportunities, and leadership quality. These attributes are found to predict job separation and exits from the labour market in heterogeneous ways and to be moderated by the availability of outside options. Overall, the results underline the multiple costs and benefits associated with experienced job quality, which are particularly important to acknowledge in a context characterised by labour supply shortages. The final section discusses avenues for future research, highlights broader policy implications, and concludes the dissertation.

Essays on Job Quality: Agglomeration, Green Jobs and Labour Turnover

LUNARDON, DAVIDE
2026

Abstract

This dissertation contributes to the empirical literature on job quality. The first chapter introduces the broader debate and presents the overall structure of the thesis. The second chapter examines the implications of agglomeration for job quality using an urban–rural comparative approach across multiple indicators. The results show that rural workers are better off in terms of work intensity and job satisfaction, while urban workers benefit from stronger job-match opportunities. Overall, the findings support the view that adopting a job quality lens can usefully complement assessments of the welfare desirability of urbanization. The third chapter investigates the intrinsic value that workers derive from performing occupations that include tasks beneficial to the environment- so-called green jobs- using the concept of meaningful work. The analysis confirms that workers gain intrinsic value from green jobs, conditional on the broader social-norms/policy-context. The favourable labour supply responses associated with meaningful work suggest that workers should be considered a key lever for achieving the green transition. The fourth chapter analyses how poor evaluations of job attributes predict labour turnover, highlighting the particular role of intangible job attributes, measured through indicators such as interesting work, learning opportunities, and leadership quality. These attributes are found to predict job separation and exits from the labour market in heterogeneous ways and to be moderated by the availability of outside options. Overall, the results underline the multiple costs and benefits associated with experienced job quality, which are particularly important to acknowledge in a context characterised by labour supply shortages. The final section discusses avenues for future research, highlights broader policy implications, and concludes the dissertation.
8-giu-2026
Inglese
MARZUCCHI, ALBERTO
Gran Sasso Science Institute
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/374087
Il codice NBN di questa tesi è URN:NBN:IT:GSSI-374087