Mobility and the Return to Education: Testing a Roy Model with Multiple Markets

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.Selection Bias, Polychotomous Choice, Roy Model, Return to Education, Migration

Family Violence and Football: The Effect of Unexpected Emotional Cues on Violent Behavior

We study the link between family violence and the emotional cues associated with wins and losses by local professional football teams. We hypothesize that the risk of violence is affected by the 'gain-loss' utility of game outcomes around a rationally expected reference point. Our empirical analysis uses police reports of violent incidents on Sundays during the professional football season. Controlling for the pre-game point spread and the size of the local viewing audience, we find that upset losses (defeats when the home team was predicted to win by 4 or more points) lead to a 10 percent increase in the rate of at-home violence by men against their wives and girlfriends. In contrast, losses when the game was expected to be close have small and insignificant effects. Upset wins (when the home team was predicted to lose) also have little impact on violence, consistent with asymmetry in the gain-loss utility function. The rise in violence after an upset loss is concentrated in a narrow time window near the end of the game, and is larger for more important games. We find no evidence for reference point updating based on the halftime score.reference dependence, gain-loss utility, intimate partner violence

The Demand for Sons: Evidence from Divorce, Fertility, and Shotgun Marriage

This paper shows how parental preferences for sons versus daughters affect divorce, child custody, marriage, shotgun marriage when the sex of the child is known before birth, and fertility stopping rules. We document that parents with girls are significantly more likely to be divorced, that divorced fathers are more likely to have custody of their sons, and that women with only girls are substantially more likely to have never been married. Perhaps the most striking evidence comes from the analysis of shotgun marriages. Among those who have an ultrasound test during their pregnancy, mothers carrying a boy are more likely to be married at delivery. When we turn to fertility, we find that in families with at least two children, the probability of having another child is higher for all-girl families than all-boy families. This preference for sons seems to be largely driven by fathers, with men reporting they would rather have a boy by more than a two to one margin. In the final part of the paper, we compare the effects for the U.S. to five developing countries.

The Impact of Family Income on Child Achievement

Understanding the consequences of growing up poor for a child's well-being is an important research question, but one that is difficult to answer due to the potential endogeneity of family income. Past estimates of the effect of family income on child development have often been plagued by omitted variable bias and measurement error. In this paper, we use a fixed effect instrumental variables strategy to estimate the causal effect of income on children's math and reading achievement. Our primary source of identification comes 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%, or approximately $2,100. Using a panel of over 6,000 children matched to their mothers from National Longitudinal Survey of Youth datasets allows us to address problems associated with unobserved heterogeneity and endogenous transitory income shocks as well as measurement error in income. Our baseline estimates imply that a$1,000 increase in income raises math test scores by 2.1% and reading test scores by 3.6% of a standard deviation. The results are even stronger when looking at children from disadvantaged families who are affected most by the large changes in the EITC, and are robust to a variety of alternative specifications.

Early Teen Marriage and Future Poverty

Both early teen marriage and dropping out of high school have historically been associated with a variety of negative outcomes, including higher poverty rates throughout life. Are these negative outcomes due to pre-existing differences or do they represent the causal effect of marriage and schooling choices? To better understand the true personal and societal consequences, this paper uses an instrumental variables approach which takes advantage of variation in state laws regulating the age at which individuals are allowed to marry, drop out of school, and begin work. The baseline IV estimate indicates that a woman who marries young is 31 percentage points more likely to live in poverty when she is older. Similarly, a woman who drops out of school is 11 percentage points more likely to be poor. The results are robust to a variety of alternative specifications and estimation methods, including LIML estimation and a control function approach. While grouped OLS estimates for the early teen marriage variable are also large, OLS estimates based on individual-level data are small, consistent with a large amount of measurement error.