innovational outliers, within a forecasting framework for macroeconomic variables. Drawing on data from the COVID-19 pandemic, the … outperform both those with innovational outlier corrections and no outlier corrections in forecasting post-pandemic household …-lived extreme observations, as in the case of pandemics. These results carry important implications for macroeconomic forecasting …

forests to estimate our forecasting models. As an extension, we report empirical evidence on the predictive value of the …

forecasts. However, demand outliers across or in parts of a network complicate accurate demand forecasting, and the network …

the LISAR model against competing models on synthetic data, showing that LISAR outperforms in forecasting accuracy and … equally good for up to 91% of the time series under consideration in terms of forecasting accuracy. We show in this study … higher accuracy, better forecasting results, and improves the understanding of market movements and sectoral structures. …

their forecasting performance. Our findings reveal significant heterogeneity in ETM volatility patterns, which challenge …

Allocation algorithm. For the forecasting experiment, we select 10 sign-adjusted topics that show strong correlations with GDP … information beyond professional forecasts. In an out-of-sample forecasting experiment, we also find that combining Dynamic Factor … solely on hard data across all forecasting horizons, with the greatest improvements seen in nowcasts. These results …