Wie sich die bei den Geschlechtern unterschiedliche Bereitschaft zu längeren Fahrtstrecken auf den Lohn und damit den Gender Pay Gap auswirkt

Eine Studie behandelt, wie sich die Bereitschaft zu längeren Fahrtzeiten sich auf den Gender Pay Gap auswirkt:

We relate gender differences in willingness to commute to the gender wage gap. Using French administrative data on job search criteria, we first document that unemployed women have a lower reservation wage and a shorter maximum acceptable commute than their male counterparts. We identify indifference curves between wage and commute using the joint distributions of reservation job attributes and accepted job bundles. Indifference curves are steeper for women, who value commute around 20% more than men. Controlling in particular for the previous job, newly hired women are paid after unemployment 4% less per hour and have a 12% shorter commute than men. Through the lens of a job search model where commuting matters, we estimate that gender differences in commute valuation can account for a 0.5 log point hourly wage deficit for women, that is, 14% of the residualized gender wage gap. Finally, we use job application data to test the robustness of our results and to show that female workers do not receive less demand from far-away employers, confirming that most of the gender gap in commute is supply-side driven.

Quelle: Gender Differences in Job Search: Trading off Commute against Wage* 

Aus der Studie:

Using a sample of around 300,000 workers, we document differences in the reservation wage and maximum acceptable commute specified by men versus women. The data are combined with matched employer-employee registers such that we can precisely control for the characteristics of the previous job and check whether these differences in reported search criteria translate into differences in the attributes of the job following the unemployment spell. We find that unemployed women have a full-time equivalent reservation wage that is 4% lower than men, controlling finely for the previous job (wage bins, three-digit occupation, etc.) and the job opportunities available (commuting zone times industry times quarter fixed effects). Women also search for jobs located closer to home. The gender gap in the maximum acceptable commute is 14% on average: from 8% for single individuals without children to 24% for married individuals with children. These gender differences in reservation job attributes translate into women getting paid lower wages and having a shorter commute upon reemployment.

Wenig überraschend wollen Frauen mit Kindern möglichst nahe an ihrem Wohnort arbeiten, schon weil sie wahrscheinlich dann auch die Kinder abholen etc. und das dann auch bedeutet, dass sie letztendlich zum einen mehr arbeiten können (wenn sie zB die Kinder um 2 Uhr aus dem Kindergarten abholen wollen, dann müssen sie natürlich bei einer Stunde Fahrzeit früher los als bei 10 Minuten Fahrzeit. Sie können auch schneller reagieren, wenn das Kind abgeholt werden muss etc.

Aus der Studie:

Table II provides evidence that women are less demanding than men on the wage dimension but more demanding on the commute dimension. In our preferred specification, women specify a 4% lower reservation wage than men, while their stated maximum acceptable commute is 14% lower than that of comparable men. Online Appendix Table D3 reports gender differences in occupation and working hours. Women and men have almost the same propensity to search for a job in the same occupation as the one they held previously (the gender gap is less than 0.7 percentage points). Consistent with previous research, women have a higher propensity to look for a part-time job than men—by 6.5 percentage points. Hence columns (3) and (4) test whether the gender gaps in reservation wage and in reservation commute survive when we control for the difference in preferred working hours. We find that they are barely affected by gender differences in the preference for part-time work. Columns (5) and (6) show that removing all controls related to the previous work history (and other search criteria) increases the gap to 7% for the reservation wage and 17% for the reservation commute.

Table III shows that gender gaps in reemployment outcomes closely follow the gender gaps in search criteria. Even when controlling finely for the previous job characteristics, the gender wage gap amounts to 4% (column (1)), and the gender commute gap to 12% (column (2)). These differences survive when we control for other attributes of the new job in columns (3) and (4): part-time, type of contract, and change of occupation. In columns (5) and (6), we control for the search criteria (reservation wage, maximum acceptable commute, and others). With the search-related controls, magnitudes are roughly halved: the gender wage gap amounts to 2% and the gender commute gap to 5%. Columns (7) and (8) show that the gender gaps double when removing all controls related to the previous work history to 8% for wages and 24% for commuting distances. The parallel between Tables II and III builds confidence in the validity of the answers to the search strategy questions asked by the French PES. Moreover, it suggests that gender gaps in realized job outcomes are partly driven by labor supply. This is further hinted at in the heterogeneity analyses in Section III.B.

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Overall, the decomposition results rank gender differences in WTP for a shorter commute as an important driver of the gender wage gap. Mas and Pallais (2017) find that “with a 20 percent compensating differential for both work at home and working a fixed schedule instead of an irregular one, the differences by gender in the prevalence of these arrangements would only lead to a 1.7 percent raw gender wage gap or a 2.0 percent gap with controls.” Wiswall and Zafar (2017) find that gender differences in students’ preferences for future earnings growth, probability of dismissal, and working-hours flexibility, account for one quarter of the gender earnings gap. Bertrand, Goldin, and Katz (2010) find that for MBA graduates, 30% of the gender wage gap is accounted for by gender differences in hours of work a week.