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 …

This accessible textbook introduces the foundations of applied econometrics and statistics for undergraduate students …. It covers key topics in econometrics by using step-by-step examples in Gretl and R, providing a guide to using … and isolating effects, instrumental variables, dummy variables, non-linear effects, probability models, heteroskedasticity …

. The endogeneity problem is treated with the method of identification through heteroskedasticity as described by Rigobon …

with Generalised AutoRegressive Conditional Heteroskedasticity are characterised by the ability to estimate and forecast …