Estimating the health impacts of food safety interventions: Optimal counterfactual selections via information criteria in small samples

This paper provides a case study to show how researchers can apply an innovative counterfactual approach for food safety policy evaluations, particularly in small samples. As an extension to prior studies, I utilize comprehensive variable selection algorithms and generate the optimal combination of counterfactuals. To illustrate the method, I measured public health impacts of a historical food safety intervention. Significant health benefit was found associated with implementation of large-scale milk safety regulation in Chicago.