J24 Human Capital; Skills; Occupational Choice; Labor Productivity
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We examine how the gender of business-owners is related to the wages paid to female relative to male employees working in their firms. Using Finnish register data and employing firm fixed effects, we find that the gender pay gap is – starting from a gender pay gap of 11 to 12 percent - two to three percentage-points lower for hourly wages in female-owned firms than in male-owned firms. Results are robust to how the wage is measured, as well as to various further robustness checks. More importantly, we find substantial differences between industries. While, for instance, in the manufacturing sector, the gender of the owner plays no role for the gender pay gap, in several service sector industries, like ICT or business services, no or a negligible gender pay gap can be found, but only when firms are led by female business owners. Businesses in male ownership maintain a gender pay gap of around 10 percent also in the latter industries. With increasing firm size, the influence of the gender of the owner, however, fades. In large firms, it seems that others – firm managers – determine wages and no differences in the pay gap are observed between male- and female-owned firms.
While inequality of opportunity (IOp) in earnings is well studied, the literature on IOp in individual net wealth is scarce to non-existent. This is problematic because both theoretical and empirical evidence show that the position in the wealth and income distribution can significantly diverge.We measure ex-ante IOp in net wealth for Germany using data from the Socio-Economic Panel (SOEP). Ex-ante IOp is defined as the contribution of circumstances to the inequality in net wealth before effort is exerted. The SOEP allows for a direct mapping from individual circumstances to individual net wealth and for a detailed decomposition of net wealth inequality into a variety of circumstances; among them childhood background, intergenerational transfers, and regional characteristics. The ratio of inequality of opportunity to total inequality is stable from 2002 to 2019. This is in sharp contrast to labor earnings, where ex-ante IOp is declining over time. Our estimates suggest that about 62% of the inequality in net wealth is due to circumstances. The most important circumstances are intergenerational transfers, parental occupation, and the region of birth. In contrast, gender and individuals’ own education are the most important circumstances for earnings.
On Track to Success?
(2022)
Many countries consider expanding vocational curricula in secondary education to boost skills and labour market outcomes among non-university-bound students. However, critics fear this could divert other students from more profitable academic education. We study labour market returns to vocational education in England, where until recently students chose between a vocational track, an academic track and quitting education at age 16. Identification is challenging because self-selection is strong and because students’ next-best alternatives are unknown. Against this back- drop, we leverage multiple instrumental variables to estimate margin-specific treatment effects, i.e., causal returns to vocational education for students at the margin with academic education and, separately, for students at the margin with quitting education. Identification comes from variation in distance to the nearest vocational provider conditional on distance to the nearest academic provider (and vice-versa), while controlling for granular student, school and neighbourhood characteristics. The analysis is based on population-wide administrative education data linked to tax records. We find that the vast majority of marginal vocational students are indifferent be- tween vocational and academic education. For them, vocational enrolment substantially decreases earnings at age 30. This earnings penalty grows with age and is due to wages, not employment. However, consistent with comparative advantage, the penalty is smaller for students with higher revealed preferences for the vocational track. For the few students at the margin with no further education, we find merely tentative evidence of increased employment and earnings from vocational enrolment.
We provide the first estimates of the impact of managers’ risk preferences on their training allocation decisions. Our conceptual framework links managers’ risk preferences to firms’ training decisions through the bonuses they expect to receive. Risk-averse managers are expected to select workers with low turnover risk and invest in specific rather than general training. Empirical evidence supporting these predictions is provided using a novel vignette study embedded in a nationally representative survey of firm managers. Risk-tolerant and risk-averse decision makers have significantly different training preferences. Risk aversion results in increased sensitivity to turnover risk. Managers who are risk-averse offer significantly less general training and, in some cases, are more reluctant to train workers with a history of job mobility. All managers, irrespective of their risk preferences, are sensitive to the investment risk associated with training, avoiding training that is more costly or targets those with less occupational expertise or nearing retirement. This suggests the risks of training are primarily due to the risk that trained workers will leave the firm (turnover risk) rather than the risk that the benefits of training do not outweigh the costs (investment risk).
Against a background of increasing violence against non-natives, we estimate the effect of hate crime on refugees’ mental health in Germany. For this purpose, we combine two datasets: administrative records on xenophobic crime against refugee shelters by the Federal Criminal Office and the IAB-BAMF-SOEP Survey of Refugees. We apply a regression discontinuity in time design to estimate the effect of interest. Our results indicate that hate crime has a substantial negative effect on several mental health indicators, including the Mental Component Summary score and the Patient Health Questionnaire-4 score. The effects are stronger for refugees with closer geographic proximity to the focal hate crime and refugees with low country-specific human capital. While the estimated effect is only transitory, we argue that negative mental health shocks during the critical period after arrival have important long-term consequences. Keywords: Mental health, hate crime, migration, refugees, human capital.