Credible Granger-causality analysis appears to require post-sample inference, as it is well-known that in-sample t can be a poor guide to actual forecasting e ffectiveness. But post-sample model testing requires an often-consequential a priori partitioning of the data into an `in-sample' period...

We investigate identification of causal parameters in case-control and related studies. The odds ratio in the sample is our main estimand of interest and we articulate its relationship with causal parameters under various scenarios. It turns out that the odds ratio is generally a sharp upper...