Peer and selection effects on youth smoking in California

A number of studies have indicated that peer smoking is a highly influential factor in a young person's decision to smoke. However, these results are suspect because the studies often fail to account for selection and simultaneity bias. This paper develops an econometric model of youth smoking which incorporates both peer effects and selection effects, and estimates its parameters using data on California youth. Identification is achieved by using the degree of selection on observables as a proxy for the degree of selection on unobservables. The results indicate that the influence of peers on a young person's decision to smoke is much weaker than is suggested by reduced form models.social interactions, peer effects, smoking, substance use

Simulation-based estimation of peer effects

The influence of peer behavior on an individual's choices has received renewed interest in recent years. However, accurate measures of this influence are difficult to obtain. Standard reduced-form methods lead to upwardly biased estimates due to simultaneity, common shocks, and nonrandom peer group selection. This paper describes a structural econometric model of peer effects in binary choice, as well as a simulated maximum likelihood estimator for its parameters. The model is nonparametrically identified under plausible restrictions, and can place informative bounds on parameter values under much weaker restrictions. Monte Carlo results indicate that this estimator performs better than a reduced form approach in a wide variety of settings. A brief application to youth smoking demonstrates the method and suggests that previous studies dramatically overstate peer influence.social interactions, peer effects, neighborhood effects

Peer effects and selection effects in youth smoking

social interactions, peer effects

Sorting and inequality in Canadian schools

Researchers and educators often argue that a student's peers strongly influence his or her educational outcomes. If so, an unequal distribution of advantaged and disadvantaged students across schools in a community will leave many students doubly disadvantaged and amplify existing inequalities. We explore the relationship between the degree of sorting by socioeconomic characteristics, ethnicity and language across schools within a community and inequality as measured by the variance of standardized high school exam scores within the community. Simple cross- sectional estimates suggest a direct relationship between sorting by ethnicity and the variance of test scores, but no direct relationship between sorting by income or primary parent's education and the variance of test scores. We then implement a fixed effects estimator to control for endogeneity in the extent of sorting: the results indicate that sorting by ethnicity does not affect the variance of test scores, but that sorting by home language and primary parent's education does.social interactions, peer effects, sorting, classroom effects

Sorting, Peers and Achievement of Aboriginal Students in British Columbia

We use administrative data on students in grades 4 and 7 in British Columbia to examine the extent to which differences in school environment contribute to the achievement gap between Aboriginal and non-Aboriginal students as measured by standardized test scores. We find that segregation of Aboriginal and non-Aboriginal students is substantial, and that differences in the distribution of these two groups across schools account for roughly half the overall achievement gap on the Foundation Skills Assessment tests in grade 7. The substantial school-level segregation of Aboriginal and non-Aboriginal student across schools means that Aboriginal students on average have a higher proportion of peers who are themselves Aboriginal, as well as a higher proportion of peers in special education. We estimate the effect of peer composition on value-added exam outcomes, using longitudinal data on multiple cohorts of students together with school-by-grade fixed effects to account for endogenous selection into schools. We find that having a greater proportion of Aboriginal peers, if anything, improves the achievement of Aboriginal students.Aboriginal education, peer effects

Bounding a Linear Causal Effect Using Relative Correlation Restrictions

This paper describes and implements a simple approach to the most common problem in applied microeconometrics: estimating a linear causal effct when the explanatory variable of interest might be correlated with relevant unobserved variables. The main idea is to place restrictions on the correlation between the variable of interest and relevant unobserved variables relative to the correlation between the variable of interest and observed control variables. These relative correlation restrictions allow a researcher to construct informative bounds on parameter estimates, and to assess the sensitivity of conventional estimates to plausible deviations from the identifying assumptions. The estimation method and its properties are described, and two empirical applications are demonstrated

Social Interactions, Thresholds, and Unemployment in Neighborhoods

This paper finds that the predicted unemployment rate in a community increases dramatically when the fraction of neighborhood residents with college degrees drops below twenty percent. This threshold behavior provides empirical support for ``epidemic'' theories of inner-city unemployment. Using a structural model with unobserved neighborhood heterogeneity in productivity due to sorting, I show that sorting alone cannot generate the observed thresholds without also implying an implausible shape for the wage distribution. This provides further evidence that true social interaction effects are driving the earlier results.

Bounding a linear causal effect using relative correlation restrictions

This paper describes and implements a simple approach to the most common problem in applied microeconometrics: estimating a linear causal effct when the explanatory variable of interest might be correlated with relevant unobserved variables. The main idea is to place restrictions on the correlation between the variable of interest and relevant unobserved variables relative to the correlation between the variable of interest and observed control variables. These relative correlation restrictions allow a researcher to construct informative bounds on parameter estimates, and to assess the sensitivity of conventional estimates to plausible deviations from the identifying assumptions. The estimation method and its properties are described, and two empirical applications are demonstrated.sensitivity analysis, partial identification, endogeneity

Social Interactions, Thresholds, and Unemployment in Neighborhoods

This paper finds that the predicted unemployment rate in a community increases dramatically when the fraction of neighborhood residents with college degrees drops below twenty percent. This threshold behavior provides empirical support for "epidemic" theories of inner-city unemployment. Using a structural model with unobserved neighborhood heterogeneity in productivity due to sorting, I show that sorting alone cannot generate the observed thresholds without also implying a wage distribution which is inconsistent with that observed in microeconomic data. Social interaction effects are thus a necessary element in any suitable explanation for the data.neighborhood effects; spillovers; networks; social interactions