Does Immigration Affect the Long-Term Educational Outcomes of Natives? Quasi-Experimental Evidence

This paper uses the mass migration wave to Israel in the 1990s to examine the impact of immigrant concentration in elementary school on the long-term academic outcomes of native students in high school. To identify the causal effect of immigrant children on their peers, we exploit random variation in the number of immigrants across grades within the same school. The results suggest that the overall presence of immigrants had essentially no effect on the quality of the high school attended by native Israelis and on dropout rates, and at most a mild negative effect on high school matriculation rates. However, when we break up the sample by parents' education and by ethnic origin, we find that disadvantaged children were more likely to have been adversely affected by a higher immigrant concentration in elementary school. Focusing on the impact of Ethiopian immigrants who are from a much lower socio-economic background, we find stronger evidence of adverse effects, especially for disadvantaged students and in classes where immigrant concentration was particularly high.

Sixty Years after the Magic Carpet Ride: The Long-Run Effect of the Early Childhood Environment on Social and Economic Outcomes

This paper estimates the effect of the childhood environment on a large array of social and economic outcomes lasting almost 60 years, for both the affected cohorts and for their children. To do this, we exploit a natural experiment provided by the 1949 Magic Carpet operation, where over 50,000 Yemenite immigrants were airlifted to Israel. The Yemenites, who lacked any formal schooling or knowledge of a western-style culture or bureaucracy, believed that they were being "redeemed," and put their trust in the Israeli authorities to make decisions about where they should go and what they should do. As a result, they were scattered across the country in essentially a random fashion, and as we show, the environmental conditions faced by immigrant children were not correlated with other factors that affected the long-term outcomes of individuals. We construct three summary measures of the childhood environment: 1) whether the home had running water, sanitation and electricity; 2) whether the locality of residence was in an urban environment with a good economic infrastructure; and 3) whether the locality of residence was a Yemenite enclave. We find that children who were placed in a better environment (i.e. with better sanitary and infrastructure conditions) were more likely to obtain higher education, marry at an older age, have fewer children, and work at age 55. They were also more likely to be assimilated into Israeli society, to be less religious, and have more worldly tastes in music and food. The estimated effects are much more pronounced for women than for men. We find weaker and somewhat mixed effects on health outcomes, and no effect on political views. We do find an effect on the next generation – children who lived in a better environment grew up to have children who achieved higher educational attainment.

Infinite mixture-of-experts model for sparse survival regression with application to breast cancer

BACKGROUND: We present an infinite mixture-of-experts model to find an unknown number of sub-groups within a given patient cohort based on survival analysis. The effect of patient features on survival is modeled using the Cox's proportionality hazards model which yields a non-standard regression component. The model is able to find key explanatory factors (chosen from main effects and higher-order interactions) for each sub-group by enforcing sparsity on the regression coefficients via the Bayesian Group-Lasso. RESULTS: Simulated examples justify the need of such an elaborate framework for identifying sub-groups along with their key characteristics versus other simpler models. When applied to a breast-cancer dataset consisting of survival times and protein expression levels of patients, it results in identifying two distinct sub-groups with different survival patterns (low-risk and high-risk) along with the respective sets of compound markers. CONCLUSIONS: The unified framework presented here, combining elements of cluster and feature detection for survival analysis, is clearly a powerful tool for analyzing survival patterns within a patient group. The model also demonstrates the feasibility of analyzing complex interactions which can contribute to definition of novel prognostic compound markers

Waiting for Mr Right: Rising Inequality and Declining Marriage Rates

This Paper demonstrates that women search longer for their first or second husband in cities with higher male wage inequality, and analyses several explanations for this result. A causal link is established by showing that the results are robust to the inclusion of city fixed-effects and city-specific time trends, and by using inequality in the woman’s state of birth as a proxy for the local level of male inequality. Increasing male inequality explains about 30% of the marriage rate decline for women over the last few decades, and we show that this is not due to the effects of male inequality on female inequality, female labour supply, or decisions by women to re-locate, nor to the decisions of men in reaction to changes in their own wages. The evidence supports the idea that higher male inequality increases the option value for single women to search longer for a husband.inequality; marriage; search