We use a novel research design to empirically detect the effect of social interactions among neighbors on labor market outcomes. Specifically, using Census data that characterize residential and employment locations down to the city block, we examine whether individuals residing in the same block are more likely to work together than those in nearby blocks. We find evidence of significant social interactions operating at the block level: residing on the same versus nearby blocks increases the probability of working together by over 33 percent. The results also indicate that this referral effect is stronger when individuals are similar in socio-demographic characteristics (e.g., both have children of similar ages) and when at least one individual is well attached to the labor market. These findings are robust across various specifications intended to address concerns related to sorting and reverse causation. Further, having determined the characteristics of a pair of individuals that lead to an especially strong referral effect, we provide evidence that the increased availability of neighborhood referrals has a significant impact on a wide range of labor market outcomes including labor force participation, hours and earnings.

SUMMARYThis paper examines the spatial patterns of unemployment in Chicago between 1980 and 1990. We study unemployment clustering with respect to different social and economic distance metrics that reflect the structure of agents' social networks. Specifically, we use physical distance, travel time, and differences in ethnic and occupational distribution between locations. Our goal is to determine whether our estimates of spatial dependence are consistent with models in which agents' employment status is affected by information exchanged locally within their social networks. We present non-parametric estimates of correlation across Census tracts as a function of each distance metric as well as pairs of metrics, both for unemployment rate itself and after conditioning on a set of tract characteristics. Our results indicate that there is a strong positive and statistically significant degree of spatial dependence in the distribution of raw unemployment rates, for all our metrics. However, once we condition on a set of covariates, most of the spatial autocorrelation is eliminated, with the exception of physical and occupational distance. Racial and ethnic composition variables are the single most important factor in explaining the observed correlation patterns.

This paper presents an empirical analysis of a choice-theoretic model of cultural transmission. In particular, we use data from the General Social Survey to estimate the structural parameters of a model of marriage and child socialization along religious lines in the United States. The observed intermarriage and socialization rates are consistent with Protestants, Catholics, and Jews having a strong preference for children who identify with their own religious beliefs and making costly decisions to influence their children's religious beliefs. Our estimates imply dynamics of the shares of religious traits in the population that are in sharp contrast with the predictions obtained by linear extrapolations from current intermarriage rates.

We use a novel research design to empirically detect the effect of social interactions on labor market outcomes. Using Census data on residential and employment locations, we examine whether individuals residing in the same city block are more likely to work together than those in nearby blocks. We find evidence of significant social interactions. The estimated referral effect is stronger when individuals are similar in sociodemographic characteristics. These findings are robust across specifications intended to address sorting and reverse causation. Further, the increased availability of neighborhood referrals has a significant impact on a wide range of labor market outcomes. (c) 2008 by The University of Chicago. All rights reserved..

This paper evaluates whether microcredit programs such as the popular Grameen Bank reach the relatively poor and vulnerable in two Bangladeshi villages. It uses a unique panel dataset with monthly consumption and income data for 229 households before they received loans. We …nd that while microcredit is successful at reaching the poor, it is less successful at reaching the vulnerable. Our results also suggest that microcredit is unsuccessful at reaching the group most prone to destitution, the vulnerable poor. Our main contribution is to explicitly evaluate the targeting of an anti-poverty intervention using the e¢cient risk-sharing framework in Townsend (1994).JEL Codes: O16, I38, Q12