I already posed this question some time ago, but I would like to revisit the topic with the current information and papers available. I would like to ask you what macroeconomists are doing to cope with the COVID crisis period when estimating models (DSGE, VAR or VECM).
I’m not thinking about forecasting but rather about causality analysis. For example, what if I want to conduct a simple cointegration analysis or obtain Impulse Response Functions with a stationary SVAR? What are the recommended ways to handle outliers in data generated by the COVID crisis? Does anyone have references other than Lenza and Primiceri (2020)?
I’m sure it’s a question that doesn’t have a correct or unique answer, but I believe it’s a debate in which we all are interested in finding the best approach.