Since my last two blog posts on binary and continuous inverse probability weights (IPWs) and marginal structural models (MSMs) for time-series cross-sectional (TSCS) panel data, I’ve spent a ton of time trying to figure out why I couldn’t recover the exact causal effect I had built in to those examples when using panel data. It was a mystery, and it took weeks to figure out what was happening.