forecasting power of these models for the Japanese economy. In this paper, we aim at assessing the relative performance of factor …. For most of the components, we report that factor models yield lower forecasting errors than a simple AR process or an … improvements in terms of forecasting accuracy are found for more volatile periods, such as the recent financial crisis. However …

across different horizons and real-time datasets. To further improve performances when forecasting with machine learning, we …

notably with the pandemic. In a VAR, allowing the errors to have a distribution with fatter tails than the Gaussian one equips … the model to better deal with the COVID-19 shock. A standard Gaussian VAR can still be used for producing conditional …

forecasting together with cross-equation accounting identities. A pseudo real-time forecasting exercise indicates that the model … outperforms various benchmarks, such as quarterly time series models and bridge equations in forecasting growth in quarterly GDP …

across different horizons and real-time datasets. To further improve performances when forecasting with machine learning, we …

forecasting euro area manufacturing production. Following Boivin and Ng (2006), the emphasis is put on the role of dataset …