Personality and labour market outcomes

Abstract

This thesis focuses on the role of personality in the labour market. The four empirical studies illustrate how individual characteristics are related to labour market outcomes, particularly earnings, employment and unemployment. The empirical studies are preceded by an introductory chapter in which the background, prior evidence and main results of the thesis are presented. Chapter 2 analyses the connections between personality, the decision to drop out from education and labour market outcomes. With data drawn from the Jyväskylä Longitudinal Study of Personality and Social Development JYLS, we found that dropping out was associated with weaker labour market performance over a long period of time. When the model was augmented with personality, the connection was reduced. Therefore dropouts seem to have or lack non-cognitive characteristics that are associated with labour market success. Chapter 3 illustrates the connections between personality and labour market income based on JYLS. The results suggest that adulthood extraversion is positively associated with income when education, work experience and unemployment history, measured prospectively from longitudinal data, are controlled for. Chapter 4 considers the relationship between personality and unemployment. Utilising data drawn from JYLS, we found that Big Five openness to experience was positively associated with both the duration of cumulative unemployment and the number of unemployment spells between ages 33 and 50. We also found that neuroticism was associated with longer durations of single unemployment spells. However, this result might be at least partly driven by reverse causality. Chapter 5 presents a statistical profiling system, based on micro-level data drawn from the Finnish Employment Register that aims to identify the potential long-term unemployed. The out-of-sample results suggest that compared to random and deterministic allocation methods, the statistical profiling model was clearly better at identifying those individuals with the longest durations of unemployment.