This paper considers factor estimation from heterogenous data, where some of the variables are noisy and only weakly informative for the factors. To identify the irrelevant variables, we search for zero rows in the loadings matrix of the factor model. To sharply separate these irrelevant...

The COVID-19 pandemic has led to enormous data movements that strongly affect parameters and forecasts from standard VARs. To address these issues, we propose VAR models with outlier-augmented stochastic volatility (SV) that combine transitory and persistent changes in volatility. The resulting...

To simultaneously consider mixed-frequency time series, their joint dynamics, and possible structural changes, we introduce a time-varying parameter mixed-frequency VAR. To keep our approach from becoming too complex, we implement time variation parsimoniously: only the intercepts and a common...