estimator that has become popular in applied econometrics, and conclude that its use in this context cannot be generally …

strategies that combine econometrics and machine learning when conducting forecasts with new big data sources. Specifically … reduction strategies and traditional econometrics approaches in forecast accuracy, there are further significant gains from …

In structural vector autoregressive analysis identifying the shocks of interest via heteroskedasticity has become a … standard tool. Unfortunately, the approaches currently used for modelling heteroskedasticity all have drawbacks. For instance … used conventional identification schemes in this context are rejected by the data if heteroskedasticity is allowed for …