1. Flooded Communities: Using the Post-Katrina Migration to Estimate Contextual Effects Daniel Hopkins Ph.D. Candidate Department of Government Harvard University Introduction: Overcoming the Selection Bias that Plagues Contextual Studies Using Differences-in-Differences to Rule Out Community Fixed Effects Scholars have long inquired about the impact of inter-group contact and proximity. Yet observational studies in this field are commonly plagued by selection bias and measurement error. This research uses the post-Katrina migration as an exogenous demographic shock to measure how meeting or living near members of a different group shapes people’s political views. Drawing on a new, clustered phone survey of 3,879 residents in the U.S. South, the analysis first used propensity score matching to pair respondents who came into contact with evacuees with highly similar individuals who happened to live outside the affected area. This matching procedure significantly strengthens the claim of ignorability — that the potential outcomes are independent of the treatment conditional on the covariates—since people in affected communities are being compared to the people who would have made contact had their community been affected. Propensity Score Matching: The Small and Negative Influence of Evacuee Contact On account of the exogenous shock that affected people in some areas but not others, it is possible through matching to find a control group of 381 in unaffected communities that was virtually identical at baseline to the treated group, as shown below. Estimating two sets of OLS regressions—one for the matched sample of 762, the other for the full sample of 1,605—I find that those who had contact with the evacuees show few attitudinal differences. The differences we do observe are in a negative direction, as those who had contact became less supportive of spending on the poor. A sample set of regression coefficients is below on the left, alongside the estimated impact of contact on ten dependent variables of interest. Regression coefficients for support for anti-poverty spending Treatment effects and 95% confidence intervals of inter- group contact for several evacuee-related attitudes The Negative Effects of Living in a Host Community The central conclusion: those who lived in a community that took in evacuees became more supportive of spending to fight crime, or else less supportive of anti-poverty spending. An alternative explanation is that the observed differences affected everyone in the community, not just those who made contact. With U.S. Postal Service data on evacuee relocation, I estimated the impact of living in any community that took in more than 1 evacuee per 200 residents, as shown in the map on the left. Using OLS models specified as below with standard errors clustered by ZIP code and multiple imputation, we see that those in affected communities became more supportive of anti-crime spending and less supportive of anti-poverty spending. Notice also the community-specific effects, since Houston became anti-crime while Baton Rouge became anti-poor. Treatment effects of living in a community that took in many evacuees for key attitudes The central assumption underpinning these analyses is that living in an affected community shapes attitudes only through exposure to evacuees once we take covariates into account. To relax that assumption, I used 416 respondents to the 2004 NES to simulate pre-Katrina attitudes for the treatment and control groups. Subtracting the 2006 estimated treatment effect from the 2004 difference, we have a differences-in- differences estimate which accounts for pre-existing community effects. Even doing so, we reaffirm the earlier findings. Respondents in Houston became more supportive of anti-crime spending, and respondents in Baton Rouge became less supportive of spending on the poor. The classical approach compares respondents in the first column, while this research compares respondents in the first row Each point represents one respondent to the 2006 Social Capital Community Benchmark Survey