In: Empirical Economics, 2015, vol. 49, no. 1, p. 1-31
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In: Journal of Business & Economic Statistics, 2019, p. 1-15
This article suggests a causal framework for separating individual-level treatment effects and spillover effects such as general equilibrium, interference, or interaction effects related to treatment distribution. We relax the stable unit treatment value assumption assuming away treatment-dependent interaction between study participants and permit spillover effects within aggregates, for...
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In: Empirical economics, 2015, vol. 49, no. 1, p. 1-31
Using a simulation design that is based on empirical data, a recent study by Huber et al. (J Econom 175:1–21, 2013) finds that distance-weighted radius matching with bias adjustment as proposed in Lechneret et al. (J Eur Econ Assoc 9:742–784, 2011) is competitive among a broad range of propensity score-based estimators used to correct for mean differences due to observable covariates. In...
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(Working Papers SES ; 481)
This paper suggests a causal framework for disentangling individual level treatment effects and interference effects, i.e., general equilibrium, spillover, or interaction effects related to treatment distribution. Thus, the framework allows for a relaxation of the Stable Unit Treatment Value Assumption (SUTVA), which assumes away any form of treatment-dependent interference between study...
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