Identifying Individual and Group Effects in the Presence of Sorting: A Neighborhood Effects Application

Researchers have long recognized that the non-random sorting of individuals into groups generates correlation between individual and group attributes that is likely to bias naive estimates of both individual and group effects. This paper proposes a non-parametric strategy for identifying these effects in a model that allows for both individual and group unobservables, applying this strategy to the estimation of neighborhood effects on labor market outcomes. The first part of this strategy is guided by a robust feature of the equilibrium in the canonical vertical sorting model of Epple and Platt (1998), that there is a monotonic relationship between neighborhood housing prices and neighborhood quality. This implies that under certain conditions a non- parametric function of neighborhood housing prices serves as a suitable control function for the neighborhood unobservable in the labor market outcome regression. The second part of the proposed strategy uses aggregation to develop suitable instruments for both exogenous and endogenous group attributes. Instrumenting for each individual's observed neighborhood attributes with the average neighborhood attributes of a set of observationally identical individuals eliminates the portion of the variation in neighborhood attributes due to sorting on unobserved individual attributes. The neighborhood effects application is based on confidential microdata from the 1990 Decennial Census for the Boston MSA. The results imply that the direct effects of geographic proximity to jobs, neighborhood poverty rates, and average neighborhood education are substantially larger than the conditional correlations identified using OLS, although the net effect of neighborhood quality on labor market outcomes remains small. These findings are robust across a wide variety of specifications and robustness checks.

Tribalism as a Minimax-Regret Strategy: Evidence from Voting in the 2007 Kenyan Elections

Although many studies find that voting in Africa approximates an ethnic census in that voting is primarily along ethnic lines, hardly any of the studies have sought to explain ethnic voting following a rational choice framework. Using data of voter opinions from a survey conducted two weeks before the December 2007 Kenyan elections, we find that the expected benefits associated with a win by each of the presidential candidates varied significantly across voters from different ethnic groups. We hypothesize that decision to participate in the elections was influenced by the expected benefits as per the minimax-regret voting model. We test the predictions of this model using data of voter turnout in the December 2007 elections and find that turnout across ethnic groups varied systematically with expected benefits. The results suggest that individuals participated in the elections primarily to avoid the maximum regret should a candidate from another ethnic group win. The results therefore offer credence to the minimax regret model as proposed by Ferejohn and Fiorina (1974) and refute the Downsian expected utility model.