Valid Inference on Functions of Causal Effects in the Absence of Microdata

Abstract: Economists are often interested in functions of multiple causal effects, a leading example of which is evaluating a policy's cost-effectiveness. The benefits and costs might be captured by multiple causal effects and aggregated into a scalar measure of cost-effectiveness. Oftentimes, the microdata underlying these estimates is inaccessible; only published estimates and their corresponding standard errors are available. We provide a method to conduct inference on non-linear functions of causal effects when the only information available is the point estimates and their standard errors. We apply our method to inference for the Marginal Value of Public Funds (MVPF) of government policies.