Do parents have preferences over the gender of their children, and if so, does this have negative consequences for daughters versus sons? In this paper, we show that child gender affects the marital status, family structure, and fertility of a significant number of American families. Overall, a first-born daughter is significantly less likely to be living with her father compared to a first-born son. Three factors are important in explaining this gap. First, women with first-born daughters are less likely to marry. Strikingly, we also find evidence that the gender of a child "in utero "affects shotgun marriages. Among women who have taken an ultrasound test during pregnancy, mothers who have a girl are less likely to be married at delivery than those who have a boy. Second, parents who have first-born girls are significantly more likely to be divorced. Third, after a divorce, fathers are much more likely to obtain custody of sons compared to daughters. These three factors have serious negative income and educational consequences for affected children. What explains these findings? In the last part of the paper, we turn to the relationship between child gender and fertility to help sort out parental gender bias from competing explanations for our findings. We show that the number of children is significantly higher in families with a first-born girl. Our estimates indicate that first-born daughters caused approximately 5500 more births per year, for a total of 220,000 more births over the past 40 years. Taken individually, each piece of empirical evidence is not sufficient to establish the existence of parental gender bias. But taken together, the weight of the evidence supports the notion that parents in the U.S. favour boys over girls. Copyright © 2008 The Review of Economic Studies Limited.

Past estimates of the effect of family income on child development have often been plagued by endogeneity and measurement error. In this paper, we use two simulated instrumental variables strategies to estimate the causal effect of income on children's math and reading achievement. Our identification derives from the large, non-linear changes in the Earned Income Tax Credit (EITC) over the last two decades. The largest of these changes increased family income by as much as 20 percent, or approximately $2,100. Using a panel of almost 5,000 children matched to their mothers from National Longitudinal Survey of Youth datasets allows us to address problems associated with unobserved heterogeneity, endogenous transitory income shocks, and measurement error in income. Our baseline estimates imply that a $1,000 increase in income raises combined math and reading test scores by 6 percent of a standard deviation in the short run. The gains are larger for children from disadvantaged families and are robust to a variety of alternative specifications. We find little evidence of long-run income effects, with most of the effects disappearing after one year.

Self-selected migration presents one potential explanation for why observed returns to a college education in local labor markets vary widely even though U.S. workers are highly mobile. To assess the impact of self-selection on estimated returns, this paper first develops a Roy model of mobility and earnings where workers choose in which of the 50 states (plus the District of Columbia) to live and work.Available estimation methods are either infeasible for a selection model with so many alternatives or place potentially severe restrictions on earnings and the selection process. This paper develops an alternative econometric methodology which combines Lee's (1983) parametric maximum order statistic approach to reduce the dimensionality of the error terms with more recent work on semiparametric estimation of selection models (e.g., Ahn and Powell, 1993). The resulting semiparametric correction is easy to implement and can be adapted to a variety of other polychotomous choice problems. The empirical work, which uses 1990 U.S. Census data, confirms the role of comparative advantage in mobility decisions. The results suggest that self-selection of higher educated individuals to states with higher returns to education generally leads to upward biases in OLS estimates of the returns to education in state-specific labor markets. While the estimated returns to a college education are significantly biased, correcting for the bias does not narrow the range of returns across states. Consistent with the finding that the corrected return to a college education differs across the U.S., the relative state-to-state migration flows of college-versus high school-educated individuals respond strongly to differences in the return to education and amenities across states.

Family violence is a pervasive and costly problem, yet there is no consensus on how to interpret the phenomenon of violence by

Past estimates of the effect of family income on child development have often been plagued by endogeneity and measurement error. In this paper, we use two simulated instrumental variables strategies to estimate the causal effect of income on children's math and reading achievement. Our identification derives from the large, non-linear changes in the Earned Income Tax Credit (EITC) over the last two decades. The largest of these changes increased family income by as much as 20 percent, or approximately $2,100. Using a panel of almost 5,000 children matched to their mothers from National Longitudinal Survey of Youth datasets allows us to address problems associated with unobserved heterogeneity, endogenous transitory income shocks, and measurement error in income. Our baseline estimates imply that a $1,000 increase in income raises combined math and reading test scores by 6 percent of a standard deviation in the short run. The gains are larger for children from disadvantaged families and are robust to a variety of alternative specifications. We find little evidence of long-run income effects, with most of the effects disappearing after one year.

We estimate peer effects in paid paternity leave in Norway using a regression discontinuity design. Coworkers Economists and policymakers are keenly interested in understanding the effects of social interactions on individual behavior. One question of particular interest is how peer groups influence the take-up of government social programs. Peer groups could serve as important information transmission networks or be influential in changing social norms, particularly in settings where information is scarce and perceptions are in their formative stage. Social interactions could reinforce or offset the direct effects on take-up due to a program's parameters, leading to a long-run equilibrium take-up rate which is substantially lower or higher than otherwise expected.Estimating the causal effect of social interactions has proven difficult given the well-known problems of reflection, correlated unobservables, and endogenous group membership (Manski 1993). On top of these identification issues, it is often challenging to define the appropriate peer group and access data which links members of a peer group together. Early and ongoing research attempts to control for as many group characteristics as possible or use instrumental variables.1 Recognizing that estimates could still be biased, another set of papers attempts to measure peer effects by exploiting exogenous assignment to peer groups.

Understanding whether, and in what situations, time spent in prison is criminogenic or preventive has proven challenging due to data availability and correlated unobservables. This paper overcomes these challenges in the context of Norway's criminal justice system, offering new insights into how incarceration affects subsequent crime and employment. We construct a panel dataset containing the criminal behavior and labor market outcomes of the entire population, and exploit the random assignment of criminal cases to judges who differ systematically in their stringency in sentencing defendants to prison. Using judge stringency as an instrumental variable, we find that imprisonment discourages further criminal behavior, and that the reduction extends beyond incapacitation. Incarceration decreases the probability an individual will reoffend within 5 years by 27 percentage points, and reduces the number of offenses over this same period by 10 criminal charges. In comparison, OLS shows positive associations between incarceration and subsequent criminal behavior. This sharp contrast suggests the high rates of recidivism among ex-convicts is due to selection, and not a consequence of the experience of being in prison. Exploring factors that may explain the preventive effect of incarceration, we find the decline in crime is driven by individuals who were not working prior to incarceration. Among these individuals, imprisonment increases participation in programs directed at improving employability and reducing recidivism, and ultimately, raises employment and earnings while discouraging further criminal behavior. Contrary to the widely embraced 'nothing works' doctrine, these findings demonstrate that time spent in prison with a focus on rehabilitation can indeed be preventive.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. www.econstor.eu Terms of use: Documents in D I S C U S S I O N P A P E R S E R I E S ABSTRACT What Is the Case for Paid Maternity Leave?Paid maternity leave has gained greater salience in the past few decades as mothers have increasingly entered the workforce. Indeed, the median number of weeks of paid leave to mothers among OECD countries was 14 in 1980, but had risen to 42 by 2011. We assess the case for paid maternity leave, focusing on parents' responses to a series of policy reforms in Norway which expanded paid leave from 18 to 35 weeks (without changing the length of job protection). Our first empirical result is that none of the reforms seem to crowd out unpaid leave. Each reform increases the amount of time spent at home versus work by roughly the increased number of weeks allowed. Since income replacement was 100% for most women, the reforms caused an increase in mother's time spent at home after birth, without a reduction in family income. Our second set of empirical results reveals the expansions had little effect on a wide variety of outcomes, including children's school outcomes, parental earnings and participation in the labor market in the short or long run, completed fertility, marriage or divorce. Not only is there no evidence that each expansion in isolation had economically significant effects, but this null result holds even if we cumulate our estimates across all expansions from 18 to 35 weeks. Our third finding is that paid maternity leave has negative redistribution properties. The program makes regressive transfers both from ineligibles to eligibles and within the group of eligible mothers. Since there was no crowd out of unpaid leave, the extra leave benefits amounted to a pure leisure transfer, primarily to middle and upper income families. Finally, we investigate the financial costs of the extensions in paid maternity leave. We find these reforms had little impact on parents' future tax payments and benefit receipt. As a result, the large increases in public spending on maternity leave imply a considerable increase in taxes, at a cost to economic efficiency. Taken together, our findings suggest the generous extensions to paid leave were costly, had no measurable effect on outcomes and poor redistribution properties. In a time of harsh budget realities, our findings have important implications for countries that are considering future expansions or contractions in the duration of paid leave.JEL Classification: J13, J18, H42