Asymptotics for statistical treatment rules

This paper develops asymptotic optimality theory for statistical treatment rules in smooth parametric and semiparametric models. Manski (2000, 2002, 2004) and Dehejia (2005) have argued that the problem of choosing treatments to maximize social welfare is distinct from the point estimation and hypothesis testing problems usually considered in the treatment effects literature, and advocate formal analysis of decision procedures that map empirical data into treatment choices. We develop large-sample approximations to statistical treatment assignment problems in both randomized experiments and observational data settings in which treatment effects are identified. We derive a local asymptotic minmax regret bound on social welfare, and a local asymptotic risk bound for a two-point loss function. We show that certain natural treatment assignment rules attain these bounds.treatment effect; statistical decision theory; minmax regret; treatment assignment rules

The Impacts of Animal Disease Crises on the Korean Meat Market

Employing the error correction method and historical decomposition with direct acyclic graphs, we quantify the impacts of domestic and oversea animal disease crises on the Korean meat markets. We find that (a) the market partially recovered 16 months after the foot-and-mouth outbreak in 2000, and 13 months after the avian influenza and the U.S. BSE incidents in 2003; (b) animal disease outbreaks have differentiate impacts by disease type and supply chain level. Retailers likely to have windfall profits as the retail price margin increased relative to the farm and wholesale levels; and (c) disease outbreaks affect dynamic price interdependence.Animal disease outbreak, Error correction model, Direct acyclic graphs, Korean meat market, Historical Decomposition, Price margins, Livestock Production/Industries, C32, Q11, L11,