Gender und Vereinbarkeit (German Edition)

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It is well-known that women earn less than men in paid employment. The public often perceives this difference in wages as discrimination against women, and policy makers give high priority to overcoming this inequality see e. European Commission Economic and sociological research, however, has shown that the difference in wages can largely be traced back to women having different productive characteristics than men in particular different human capital endowments , choosing different occupations and working fewer hours see Altonji and Blank for a survey and Weichselbaumer and Winter-Ebmer for a meta-analysis of this strand of literature.

Yet even when accounting for these differences, a substantial part of the gender pay gap cannot be explained and is then usually assumed to reflect employer discrimination against women. Hence, if employer discrimination played a major role, the gender gap in self-employment earnings could be expected to be significantly lower than the gender wage gap in paid employment Moore There is some empirical evidence, however, suggesting that exactly the opposite is the case — both raw and unexplained gender earnings gaps seem to be higher in self-employment than in paid employment see, e.


This is somewhat puzzling, in particular as other potential sources of discrimination such as discriminating behavior of customers or capital providers do not seem to play a substantial role for self-employed women. While it is true that women generally start self-employment with less start-up capital than men and that financial constraints seem to contribute to the gender earnings gap to some extent e.

Hundley , Walker , Rybczynski , there is no conclusive evidence whether this is due to discrimination by capital lenders see, inter alia , Asiedu et al. Also discrimination by consumers does not seem to explain the self-employment gender earnings gap see Aronson : 72—73, Moore Even though there exists a large gender gap in self-employment earnings for which discrimination does not provide a satisfactory explanation, relatively few studies have attempted to explore the causes of this gap e. Hundley and Walker for the U. While the analyses by Hundley and Walker with U.

Other studies, not considering hours and housework, mostly find the segregation of men and women into different industries or occupations to be among the most important contributions to the gender earnings gap. When it comes to Germany, the empirical evidence is especially scarce.

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In an early study, Jungbauer-Gans examines the earnings gap in using the German Micro Census which, however, only provides earnings data in intervals. For the self-employed, she finds a small earnings gap which becomes larger but insignificant when attempting to correct for selection into self- employment, and does not perform a decomposition analysis. A recent survey by Gather et al. Observing that, when analyzed on their own, neither human capital nor segregation into industries nor the existence of children can explain the earnings gap, they conclude that multivariate decomposition analysis is needed to identify the determinants of earnings differences and the unexplained residual for the self-employed.

Our study attempts to fill this gap in the literature by identifying and decomposing the causes of the self-employment gender earnings gap in Germany, using the gender pay gap in paid employment as a benchmark. Utilizing a rich cross-sectional dataset with continuous information on earnings rather than earnings intervals , we analyze whether the raw and the unexplained gender earnings gap differ between self-employment and paid employment.

Our dataset provides, among others, detailed information on human capital endowments of individuals, on personal characteristics including career aspirations, on job characteristics such as working hours, working time flexibility, professional field and task profile, and on firm size. This enables us to test whether self-employed women earn less than men because they differ in productivity-related attributes or own different types of businesses.

We are also able to analyze whether it is different motivations and non-monetary aspects that contribute to the gender earnings gap, i. That said, a limitation of this rich data set is that it is only cross-sectional, so that unobserved heterogeneity can hardly be taken into account. Yet we will perform a Heckman selection correction as a robustness check in order to address the issue of selection on unobservables into self-employment or paid employment.

In order to explain the gender earnings gap one has to identify variables that differ between male and female self-employed and at the same time affect earnings in such a way that they may account for the lower female earnings.

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We then explore the impact of these variables by estimating earnings functions in section 3. Section 4 decomposes the gender earnings gap utilizing an Oaxaca-Blinder-decomposition, and section 5 concludes. The data contains information on 20, individuals from the German active labor force population excluding apprentices who are at least 15 years old and regularly work at least 10 hours per week. As paid employees we have white-collar workers, blue-collar workers and civil servants. Observations with weekly working time of hours or more are dropped for plausibility reasons.

Additionally we remove self-employed and paid employees reporting earnings in the bottom 1 percent quantile of their respective earnings distribution to exclude some extremely low values. Our sample then consists of 15, individuals who report income data and have no missing covariates. These include male and female self-employed individuals and 7, male and 6, female paid employees. It is clear from these figures that men select into self-employment much more often than women. The self-employment share among men amounts to Distribution of earnings among men and women in self- and paid employment a.

Hourly earnings are calculated by dividing gross monthly earnings by average weekly working hours times 4. Measurement of independent and explanatory variables a. We do not mean your monthly turnover or profit. Do not include child allowance, please. Total number of years of working intermissions. Not counted as intermissions are: times of further education, paid maternity leave, times of sickness. Self-employed: Years running the current business. Paid employees: Years working at the current workplace.

Average usual weekly working hours including overtime, on-call duty, etc. For 17 groups of tasks e. The number of employees includes the owner of the firm. Calculating the difference and taking men as the reference group yields a gender earnings gap of A look at the quartiles of the earnings distribution reveals that women often have relatively low earnings and that the gender earnings gap is particularly pronounced in the lower part of the distribution.

The income difference between the sexes is clearly smaller when it comes to hourly earnings, reflecting the fact that self-employed women work fewer hours than men. The earnings gap is now Unsurprisingly, women also earn less than men in paid employment. The same is true for hourly earnings, where the gender pay gap amounts to Comparing the various differentials makes clear that the gender earnings gap is larger in self-employment than in paid employment 3.

Several variables that may be responsible for the lower earnings of female self-employed have been identified in the literature see the reviews by Parker : — and Minniti : chs. These may be grouped into three categories: 1 human capital, 2 work-family balance and working hours, and 3 segregation, which can be investigated with our data 4. Descriptive statistics on the characteristics of self-employed and paid employees a.

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Working time flexibility was measured by the frequency at which interviewees were able to take family and private interests into account when scheduling working time. The number of employees reported in the firm size variable includes the owner of the firm. Turning to working experience measured as years since first holding a job , women have slightly less working experience than men in self-employment The working intermissions of self-employed men sum up to 0.

While this difference between the sexes also exists in paid employment, it is again more pronounced among the self-employed. Additionally self-employed women have less specific working experience, as indicated by a lower tenure at the current job.

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While men run their current businesses for In paid employment the gender difference is much smaller. Taken together, these findings may explain why there is a gender earnings gap and why it is larger in self-employment. Lazear points out that for entrepreneurs not only the level but also the diversity of human capital might be relevant, with more diversity inducing more income.

Entrepreneurs thus should be jacks-of-all-trades i.

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If men have a more diverse professional background than women, this could explain why they earn more in self-employment. Moreover, it could also explain why the gender earnings gap is larger in self-employment, since this diversity would not benefit men in paid employment. Table 3 shows indeed that the self-employed have a more diverse background measured as the number of changes of profession than paid employees.

However, self-employed women do not report fewer changes of profession than self-employed men, suggesting that diversity of human capital will not contribute to explaining the gender earnings gap. There are some indications that women choose self-employment in order to obtain more flexibility and to better balance work and family e. Boden , Lombard ; for a survey see Gerlach and Damhus At the same time it is plausible that the more hours and effort women spend for family and housework responsibilities, the less hours and energy they are able to spend working in their firm, hence earning less money than men whose work efforts are less confined by housework and family engagements Becker , Hundley , , Walker 6.

Self-employed men work as much as Interestingly, women in self-employment work more hours than women in paid employment, whose average weekly working time amounts to In contrast to this view, self-employment may enable women to spend more time on market work as would otherwise be possible. For instance, being their own boss, they can more easily work odd hours such as nights or weekends. However, self-employed women as well as self-employed men do not seem to be able to better balance working time scheduling with family and private interests than women respectively men in paid employment.

For instance, 66 percent of female employees and 65 percent of female self-employed state that they often succeed in taking family and private interests into account when scheduling their working time. Only 50 percent of men in self-employment often succeed in balancing work and life and 9 percent never do. This could indicate a trade-off between earnings and working time flexibility in self-employment where men and women locate at different combinations.

Being asked about their attitude towards career advancement self-employed women significantly more often stated high career aspirations than women in paid employment, namely 58 percent vs. This may indicate that women with high career aspirations choose self-employment because paid employment does not provide them with satisfactory career opportunities e. Looking at family background, we find no substantial differences in terms of living with a partner and presence of young children aged 0—5 in the household between self-employed women and women in paid employment.

Altogether these descriptive findings do not suggest that women choose self-employment primarily as a means of providing more time and energy to family and housework. That said, women clearly work less hours in self-employment than men and their working time scheduling is far more flexible. This may well explain why they earn less in self-employment, but it does not necessarily explain why the gender earnings gap is higher in self-employment. Share of self-employed men and women working in certain professional fields in percent. The figure displays those three out of 54 professional fields where most self-employed men are active in and those three professional fields where most self-employed women are active in.

The sectoral segregation of the sexes is also mirrored by the tasks they perform. We have information on 17 tasks that may occur at the work of individuals.

Why is there a gender earnings gap in self-employment? A decomposition analysis with German data

Taking nursing, parenting, healing as an example, this task is occurring at the work of 34 percent of female self-employed but is only relevant for 21 percent of self-employed men. Monitoring and governing machines, facilities or technical processes is being performed by 41 percent of male and only 24 percent of female self-employed. Remarkably women not only perform different tasks but they also face fewer different tasks at their work than men, with self-employed men performing 9. A similar difference shows up for paid employees 7.

We expect that all these facts contribute to the explanation of the gender earnings gap. We cannot say a priori , however, whether segregation should play a more important role in self- or in paid employment.

The gender lifetime earnings gap: Exploring gendered pay from the life course perspective

We now turn to exploring how the variables discussed above are related to earnings, and whether there are important differences between self-employment and paid employment. This is investigated by estimating various earnings regressions that either include a sex dummy or are run separately for men and women. As the dependent variable we use the logarithm of monthly earnings rather than hourly earnings as is usually done in wage regressions of paid employees, because we want to see to what extent gender earnings differences can be traced back to women working fewer hours, and whether this effect differs between paid employment and self-employment.

Our explanatory variables, which were already discussed in section 2, are the following: Human capital is captured by 6 dummies for educational degrees, the years of working experience, working intermissions and tenure all in linear and quadratic form , and the number of changes of profession. The amount and the flexibility of working time are captured by the logarithm of weekly working hours and by the frequency at which individuals succeeded in balancing working time scheduling with family and private interests 3 dummies.

We use a dummy for living together with a partner and a dummy for the existence of young children aged 0—5 in the household to reflect family background. We also include the interaction of these two dummies, thus differentiating between individuals with partner and young children, individuals with partner and no young children, singles with young children and singles without young children who form the reference group.

Gender und Vereinbarkeit (German Edition) Gender und Vereinbarkeit (German Edition)
Gender und Vereinbarkeit (German Edition) Gender und Vereinbarkeit (German Edition)
Gender und Vereinbarkeit (German Edition) Gender und Vereinbarkeit (German Edition)
Gender und Vereinbarkeit (German Edition) Gender und Vereinbarkeit (German Edition)
Gender und Vereinbarkeit (German Edition) Gender und Vereinbarkeit (German Edition)
Gender und Vereinbarkeit (German Edition) Gender und Vereinbarkeit (German Edition)
Gender und Vereinbarkeit (German Edition) Gender und Vereinbarkeit (German Edition)
Gender und Vereinbarkeit (German Edition) Gender und Vereinbarkeit (German Edition)

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