No abstract

This study reconsiders the phenomenon that married men earn more money than unmarried men, a key result of the research on marriage benefits. Many earlier studies have found such a “male marital wage premium.” Recent studies using panel data for the United States conclude that part of this premium is due to selection of high earners into marriage. Nevertheless, a substantial effect of marriage seems to remain. The current study investigates whether the remaining premium is really a causal effect. Using conventional fixed-effects models, previous studies statistically controlled for selection based on wage levels only. We suggest a more general fixed-effects model that allows for higher wage growth of to-be-married men. The empirical test draws on panel data from the National Longitudinal Survey of Youth (1979 to 2012). We replicate the main finding of the literature: a wage premium remains after controlling for selection on individual wage levels. However, the remaining effect is not causal. The results show that married men earn more because selection into marriage operates not only on wage levels but also on wage growth. Hence, men on a steep career track are especially likely to marry. We conclude that arguments postulating a wage premium for married men should be discarded.

Fixed effects (FE) panel models have been used extensively in the past, as those models control for all stable heterogeneity between units. Still, the conventional FE estimator relies on the assumption of parallel trends between treated and untreated groups. It returns biased results in the presence of heterogeneous slopes or growth curves that are related to the parameter of interest (e.g., selection into treatment is based on individual growth of the outcome). In this study, we derive the bias in conventional FE models and show that fixed effects individual slope (FEIS) models can overcome this problem. This is a more general version of the conventional FE model, which accounts for heterogeneous slopes or trends, thereby providing a powerful tool for panel data and other multilevel data in general. We propose two versions of the Hausman test that can be used to identify misspecification in FE models. The performance of the FEIS estimator and the specification tests is evaluated in a series of Monte Carlo experiments. Using the examples of the marital wage premium and returns to preschool education (Head Start), we demonstrate how taking heterogeneous effects into account can seriously change the conclusions drawn from conventional FE models. Thus, we propose to test for bias in FE models in practical applications and to apply FEIS if indicated by the specification tests.

Previous research suggests that household tasks prohibit women from unfolding their full earning potential by depleting their work effort and limiting their time flexibility. The present study investigated whether this relationship can explain the wage gap between mothers and nonmothers in West Germany. The empirical analysis applied fixed-effects models and used self-reported information on time use and earnings as well as monthly family and work histories from the German Socio-Economic Panel (1985-2007Wagner, Frick, & Schupp, 2007). The findings revealed that variation in reported time spent on child care and housework on a typical weekday explains part of the motherhood wage penalty, in particular for mothers of very young children. Furthermore, housework time incurred a significant wage penalty, but only for mothers. The authors concluded that policies designed to lighten women's domestic workload may aid mothers in following rewarding careers.The wage penalty for motherhood-that is, the negative effect of having children on

This study investigates whether the fertility behaviour of significant others, in particular of one's parents and siblings, affects individuals' own fertility intentions and behaviour. Using the data of three cohorts of young Germans, we test the hypothesis that 'contagion' by siblings with young children explains the transmission of fertility patterns across generations. In theory, transmission might be explained by contagion, or transmission and contagion might operate independently of each other. The results show strong evidence for the transmission of fertility intentions and behaviour from parents to their offspring. Evidence for contagion by siblings is weak and contagious effects therefore do not explain transmission.