Gender and the effect of working hours on firm-sponsored training☆
Introduction
In the past decades, part-time work has been increasing in many countries, especially for women (Boeri and van Ours, 2013). Working part-time has a variety of implications. On the one hand, it allows women to combine work and care. On the other hand, it is associated with job instability, with lower pay and fewer opportunities to make a career. One of the reasons suggested for part-time workers to have less career opportunities is that they are less likely to receive employer-sponsored training (Bassanini et al., 2007, Blundell et al., 1996). As a consequence, their productivity does not increase as much as it would have increased otherwise. If part-time work reduces on-the-job training, inequality in earnings may increase with the share of part-time workers. Therefore, studying the relationship between part-time work and employer-sponsored training is relevant from a policy point of view.
Our paper is on the extent to which part-time workers in the Netherlands receive firm-sponsored training. In our analysis we make a distinction between part-time working women and men. As far as we know, Backes-Gellner et al. (2014) is the only study that investigates gender-specific differences in the relationship between part-time employment and firm-sponsored training. Analyzing Swiss data the authors find that female workers are less likely to receive firm-sponsored training than male workers. However, there is also a part-time effect with part-timers being less likely to receive training than full-timers. This part-time training gap appears to be gender-specific. Whereas women working part-time have a similar training incidence as full-time working women, part-time working men are less likely to be trained than full-time working men. The authors argue that their findings may be due to stereotyping where employers think that men who work part-time signal a lower attachment to their job.
We present an empirical analysis of the relationship between hours of work and firm-sponsored training. We show that the negative effect of part-time work on the probability of receiving employer-sponsored training holds for male workers but not for female workers. Whereas male part-time workers are less likely to receive training, part-time working women are as likely to receive training as full-time working women. We cannot rule out the possibility of gender-working hours specific monopsony power but we speculate that the gender-specific effect of working hours on training has to do with gender-specific stereotyping. In the Netherlands, for women it is common to work part-time. More than half of the prime age female employees work part-time. Among younger and older female workers the share of part-timers is even higher. On the contrary, working part-time is a rare event for men. Except for younger and older men, the share of part-timers is below 10%. So, part-time working men are a rare breed. Therefore, because of social norms, men working part-time could send a different signal to their employer than women working part-time. This might generate a different propensity of firms to sponsor training of male part-timers than female part-timers. Nevertheless, this different propensity may also have to do with firms having more monopsony power over part-time working women than they have of part-time working men. This would allow them to reap some of the productivity-related benefits of the training of part-time working women.
Our contribution to the literature is twofold. First, as far as we know, our paper is the first one to use panel data to study whether there are gender-specific differences in the relationship between part-time work and training. An advantage over the previous literature (i.e. Backes-Gellner et al., 2014) is our ability to exploit the longitudinal nature of our data to control for individual unobserved individual characteristics. Second, we study data from a country with a high share of part-time workers. This allows us to study the relationship between part-time work and training in great detail.
Our paper is set up as follows. Section 2 provides a discussion on the nature of part-time work and describes the institutional set-up of the Dutch labor market with respect to the use of part-time work. Section 3 describes the data and the sample used in the empirical investigation. Section 4 formalizes the econometric model and clarifies the identification strategy. The estimation results are presented and discussed in Section 5. Finally, Section 6 concludes.
Section snippets
The nature of part-time work
Part-time work is often confused with flexible labor and inferior labor standards. However, the main difference between part-time jobs and flexible jobs is that part-time jobs provide flexibility to the employer and job protection to the workers while flexible jobs provide flexibility to the employer and insecurity to the worker. Part-time jobs provide flexibility to the employer in terms of allocating hours of work across the workweek or workday to meet peaks in market demand. Part-time jobs
Data description
The data used in this paper are from a new Dutch panel, the Longitudinal Internet Studies for the Social Sciences (LISS) panel. The LISS panel is collected and administered by CentERdata of Tilburg University. A representative sample of households is drawn from a population register by Statistics Netherlands and asked to join the panel by Internet interviewing. Households are provided with a computer and/or an Internet connection if they do not have one.4
Econometric modeling
We are primarily interested in understanding whether there are gender differences in the way in which working hours might affect employees’ probability of receiving firm-sponsored training. We will therefore specify and estimate a linear equation for the probability of receiving firm-sponsored training as a function of contractual working time and a set of controls capturing individual heterogeneity. The variable for the contractual working hours is potentially endogenous for several reasons.
Baseline models
Table 5 reports the estimation results in level and first differences of the linear probability model in Eq. (1), separately for men (top panel) and women (bottom panel), with contractual weekly working hours as the measure of working hours. Table 6 reports the estimation results of the same model, but using the part-time indicator as variable of primary interest.
The OLS estimator of Eq. (2) ignoring ci returns quite similar results for men and women. An increase by 1 h in the contractual weekly
Conclusions
Using longitudinal data on workers in the Netherlands and focusing on the differences between males and females, we study the effect of working hours on the propensity of firms to sponsor training of their employees. On average, both part-time working men and part-time working women are less likely to receive firm-sponsored training than their full-time working counterparts. This is still the case if we allow for observed personal characteristics to influence the probability to receive
Compliance with ethical standards
The authors declare that they have no conflict of interest.
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We thank CentERdata of Tilburg University for providing us with the LISS (Longitudinal Internet Studies for the Social sciences) panel data on which we based our empirical analysis. The LISS panel data were collected by CentERdata through its MESS project funded by the Netherlands Organization for Scientific Research. We wish also to thank Elizabeth J. Casabianca, the participants to the AIEL conference in Cagliari (September 2015), to the ZEW Research Seminar (October 2015) and two anonymous reviewers for their comments and suggestions.