Exploring some vulnerable groups in the labour marketprecarious self-employment, disability and health problems

Abstract

This dissertation sheds some new light on the situation of some vulnerable groups in the labour market: precarious self-employment in the form of necessity entrepreneurs and ‘dependent self-employed workers’ (DSE) –i.e., the workers in this particular grey zone between employment and self-employment–, disabled individuals and individuals with poor health.https://www.educacion.gob.es/teseo/teseo/almacenarInfo.do The analysis is structured in 5 chapters, being Chapter 1 devoted to present the research focus, objectives and structure. The main body is organised in 3 chapters as follows: Chapter 2 examines whether job control, job demands and job outcomes of DSE are more similar to those of the self-employed or paid employed. To this end, a psychometrically sound multidimensional scale for these 3 key constructs is developed. Chapter 3 explores self-employment earnings (as an indicator of performance) across different entrepreneurship types based on occupational status (i.e. self-employed with employees, independent own-account workers, ‘dependent self-employed workers’) and start-up motive (i.e. opportunity, necessity, and ‘hybrid opportunity-necessity’ entrepreneurs). Chapter 4 investigates the role of different types of limitations, diseases and health problems on both the probability of working and the probability of belonging to different groups (entrepreneurs, civil servants, other paid employees, unemployed, inactive individuals —home workers, early retired individuals— and students). The final chapter presents a summary of the main findings and implications of the work, and gives an outlook on future research areas on the various topics investigated in this dissertation. The empirical analysis is based on microdata drawn from the Fifth and Sixth waves of the European Working Conditions Survey –EWCS 2010 and 2015– (Eurofound) and the 2014 European Health Interview Survey (EHIS) for Spain. As regards empirical methods, exploratory and confirmatory factor analysis (EFA and CFA), linear regressions and discrete choice models (binary and multiple non-ordered) are used.