Job turnover, wage rates, and marital stability: How are they related?

This study examines the interplay between job stability, wage rates, and marital stability. We use a Dynamic Selection Control model in which young men make sequential choices about work and family and estimate the model using an approach that takes account of self-selection, simultaneity and unobserved heterogeneity. The results quantify how job stability affects wage rates, how both affect marital status, and how marital status affects earnings and job stability. The study reveals robust evidence that job changes lower wages and the likelihood of getting married and remaining married. At the same time, marriage raises wage rates and job stability. To project the sequential effects linking job change, marital status, and earnings, we simulate the impacts of shocks that raise preferences for marriage and that increase education. Feedback effects cause the simulated wage gains from marriage to cumulate over time, indicating that long-run marriage wage premiums exceed conventional short-run estimates.     

How do marital status,work effort,and wage rates interact?

How marital status interacts with men's earnings is an important analytic and policy issue, especially in the context of debates in the United States over programs that encourage healthy marriage. This paper generates new findings about the earnings-marriage relationship by estimating the linkages among flows into and out of marriage, work effort, and wage rates. The estimates are based on National Longitudinal Survey of Youth panel data, covering 23 years of marital and labor market outcomes, and control for unobserved heterogeneity. We estimate marriage effects on hours worked (our proxy for work effort) and on wage rates for all men and for black and low-skilled men separately. The estimates reveal that entering marriage raises hours worked quickly and substantially but that marriage's effect on wage rates takes place more slowly while men continue in marriage. Together; the stimulus to hours worked and wage rates generates an 18%-19% increase in earnings, with about one-third to one-half of the marriage earnings premium attributable to higher work effort. At the same time, higher wage rates and hours worked encourage men to marry and to stay married. Thus, being married and having high earnings reinforce each other over time.     

Family Structure and Economic Success Across the Life Course

This paper examines the role that family structure plays in long-run economic outcomes across the life course. Using nearly 30 years of data from the National Longitudinal Survey of Youth 1979, we find that youths who grow up with both biological parents earn more income, work more hours each week and are more likely to be married themselves as adults, compared to children raised in single-parent families. Many of these differences continue to be statistically significant even after we control for family income experienced as an adolescent. In addition, the implied size of the income transfer that children growing up with a single parent to equalize lifetime economic outcomes would need—about $42,000—is markedly larger than the income transfers now available to families in USA.     

Marriage and State-level Economic Outcomes

Past research has examined various state-level measures that predict state economic growth and other economic and social indicators. This research has largely ignored the potential role of family structure in contributing to state-level outcomes, despite the extensive literature on links between family structure and economic outcomes at the individual level. We estimated a state-level panel model and found that both the proportion of adults and the proportion of parents who are married are strongly related to important state-level economic outcomes, including economic growth, median household income, median personal income, and poverty.     

Detecting a Change in the Correlation Coefficient in a Sequence of Bivariate Normal Variables

We consider the problem of testing the hypothesis that the correlation coefficient is stable in a sequence of n observations of independent, bivariate normal random variables against the alternative that the correlation coefficient changes after an unknown point t(t < n). We propose an estimate of the changepoint t and report on power comparisons between the commonly used test for this problem and our proposed test. Some applications to finance are discussed.