This article aims to answer to what extent fertility has a causal effect on households’ economic wellbeing—an issue that has received considerable interest in development studies and policy analysis. However, only recently has this literature begun to give importance to adequate modelling...

Causal effects are usually estimated under the assumption of no interference between individuals. This assumption means that the potential outcomes for one individual are unaffected by the treatments received by other individuals. In many situations, this is not reasonable to assume. Moreover,...

Many argue that international environmental agreements (IEAs) can alter states’ cost-benefit analyses by providing crucial information about the costs of environmental degradation. Thereby, IEAs may help to effectively curb environmental pollution. However, previous attempts to empirically...

.Ancillary experiments. are a new technique whereby researchers use a completed experiment conducted by others to recover causal estimates of a randomized intervention on new outcomes. The method requires pairing new outcome data with randomized treatment

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...

In many important settings, subjects can show signicant heterogeneity in response to a stimulus or treatment". For instance, a treatment that works for the overall population might be highly ineective, or even harmful, for a subgroup of subjects with specic characteristics. Similarly, a new...

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...