Non-linear dimension reduction in factor-augmented vector autoregressions

The COVID-19 pandemic belongs to the severest health, economic and social crises in recent decades and poses the greatest challenge to the world economy since World War II. The virus has spread around the globe and paralyzed entire economic sectors and activities. For economic modeling, the COVID-19 pandemic entails dealing with huge, unprecedented outliers in datasets which adversely affect the reliability of established, mostly linear, economic models. To the detriment of those commonly used models, economic indicators and variables are prone to unanticipated movements and do not respond in the way they are supposed to. Large shifts in the level of certain variables and strong deviations from their usual paths clearly aggravate the challenge of handling large outliers within existing econometric models.