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 …

. The GMM estimators outperform SML in the presence of misspecification in terms of multiplicative heteroskedasticity. This … holds in particular for the three-stage GMM estimator. Allowing for heteroskedasticity over time increases the robustness … with respect to misspecification in terms of ultiplicative heteroskedasticity. An application to the product innovation …

We develop a vector autoregressive framework that combines an external instrument and heteroskedasticity for the … identifying information in heteroskedasticity are less efficient and tend to underestimate the effects of monetary policy. …