Problems with inferring causal relationships from nonexperimental data are briefly reviewed, and four broad classes of methods designed to allow estimation of and inference about causal parameters are described: panel regression, matching or reweighting, instrumental variables, and regression...

We show the importance of a dynamic aggregation bias in accounting for the PPP puzzle. We prove that established time-series and panel methods substantially exaggerate the persistence of real exchange rates because of heterogeneity in the dynamics of disaggregated relative prices. When...

This paper finds that the estimates of Armington elasticities (the elasticity of substitution between groups of products identified by country of origin) obtained from multilateral trade data can differ from those obtained from bilateral trade data. In particular, the former tends to be higher...

Abstract Routinely collected administrative and clinical data are increasingly being utilized for comparing quality of care outcomes between hospitals. This problem can be considered in a causal inference framework, as such comparisons have to be adjusted for hospital-specific patient case-mix,...

Conventional methods for mediation analysis generate biased results when the mediator-outcome relationship depends on the treatment condition. This article introduces a new technique, ratio-of-mediator-probability weighting (RMPW), for decomposing total effects into direct and indirect effects...

This paper presents genetic matching, a method of multivariate matching that uses an evolutionary search algorithm to determine the weight each covariate is given. Both propensity score matching and matching based on Mahalanobis distance are limiting cases of this method. The algorithm makes...

Propensity Score Matching (PSM) has become a popular approach to estimation of causal effects. It relies on the assumption that selection into a treatment can be explained purely in terms of observable characteristics (the “unconfoundedness assumption”) and on the property that balancing on...

Drawing inferences about the effects of exposures or treatments is a common challenge in many scientific fields. We propose two methods serving complementary purposes in causal inference. One can be used to estimate average causal effects, assuming ``no confounding" given measured covariates....