Continuous training, job satisfaction and gender

Abstract

Purpose – The purpose of this paper is to analyze the relationship between participation in further training courses and job satisfaction, focussing in particular on gender differences. Design/methodology/approach – Using data from the German Socio-Economic Panel (SOEP), a Probit-adapted OLS (POLS) model is employed which allows to account for individual fixed effects. The analysis controls for a variety of socio-demographic, job and firm characteristics. Findings – The authors find a difference between males and females in the correlation between training and job satisfaction which is positive for males but insignificant for females. This difference becomes even more pronounced when applying individual fixed effects. To gain insights into the reasons for this difference, the authors further investigate training characteristics by gender. The authors find that financial support and career-orientation of courses only seems to matter for the job satisfaction of men but not for the satisfaction of women. Practical implications – In Germany, financial support and career-orientation of training courses only seem to matter for the job satisfaction of men but not for the satisfaction of women. This has important implications for the investment in and outcomes of these training endeavors from both, a participant and an employer perspective. Originality/value – This paper extends the existing literature in several ways. The authors use job satisfaction as an outcome of training which comprises non-pecuniary returns in addition to monetary returns. In addition, the authors point out gender differences and examine the heterogeneity of training courses by gender. This seems important since job satisfaction processes differ to a large extent by gender and since it is well-known that training participation also differs by gender. The panel structure of the data enables a methodological advancement in terms of accounting for time-invariant unobserved heterogeneity which is likely to matter for the results.

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