Unrestricted mixed data sampling (MIDAS): MIDAS regressions with unrestricted lag polynomials C Foroni, M Marcellino, C Schumacher Journal of the Royal Statistical Society Series A: Statistics in Society 178 …, 2015 | 378 | 2015 |
A survey of econometric methods for mixed-frequency data C Foroni, MG Marcellino Available at SSRN 2268912, 2013 | 242 | 2013 |
A comparison of mixed frequency approaches for nowcasting Euro area macroeconomic aggregates C Foroni, M Marcellino International Journal of Forecasting 30 (3), 554-568, 2014 | 165 | 2014 |
Forecasting the Covid-19 recession and recovery: Lessons from the financial crisis C Foroni, M Marcellino, D Stevanovic International Journal of Forecasting 38 (2), 596-612, 2022 | 130 | 2022 |
Labor supply factors and economic fluctuations C Foroni, F Furlanetto, A Lepetit International Economic Review 59 (3), 1491-1510, 2018 | 100 | 2018 |
The impact of the COVID-19 pandemic on the euro area labour market R Anderton, V Botelho, A Consolo, AD Da Silva, C Foroni, M Mohr, ... Economic Bulletin Articles 8, 2021 | 92 | 2021 |
Using low frequency information for predicting high frequency variables C Foroni, P Guérin, M Marcellino International Journal of Forecasting 34 (4), 774-787, 2018 | 83 | 2018 |
Mixed-Frequency Vector Autoregressive Models☆ This views expressed herein are solely those of the authors and do not necessarily reflect the views of the Norges Bank. The … C Foroni, E Ghysels, M Marcellino VAR models in macroeconomics–new developments and applications: Essays in …, 2013 | 53 | 2013 |
Density forecasts with MIDAS models KA Aastveit, C Foroni, F Ravazzolo Journal of Applied Econometrics 32 (4), 783-801, 2017 | 44 | 2017 |
Mixed‐frequency structural models: Identification, estimation, and policy analysis C Foroni, M Marcellino Journal of Applied Econometrics 29 (7), 1118-1144, 2014 | 44 | 2014 |
U-MIDAS: MIDAS regressions with unrestricted lag polynomials C Foroni, MG Marcellino, C Schumacher Bundesbank Series 1 Discussion Paper, 2011 | 44 | 2011 |
Markov-switching mixed-frequency VAR models C Foroni, P Guérin, M Marcellino International Journal of Forecasting 31 (3), 692-711, 2015 | 43 | 2015 |
Explaining the time-varying effects of oil market shocks on US stock returns C Foroni, P Guérin, M Marcellino Economics letters 155, 84-88, 2017 | 37 | 2017 |
Mixed frequency structural vector auto-regressive models C Foroni, M Marcellino Journal of the Royal Statistical Society Series A: Statistics in Society 179 …, 2016 | 31 | 2016 |
Uncertainty through the lenses of a mixed-frequency Bayesian panel Markov-switching model R Casarin, C Foroni, M Marcellino, F Ravazzolo | 25 | 2018 |
Mixed‐frequency models with moving‐average components C Foroni, M Marcellino, D Stevanovic Journal of Applied Econometrics 34 (5), 688-706, 2019 | 23 | 2019 |
Short-time work schemes and their effects on wages and disposable income AD Da Silva, M Dossche, F Dreher, C Foroni, G Koester Economic Bulletin Boxes 4, 2020 | 20 | 2020 |
Assessing the predictive ability of sovereign default risk on exchange rate returns C Foroni, F Ravazzolo, B Sadaba Journal of International Money and Finance 81, 242-264, 2018 | 17 | 2018 |
A daily indicator of economic growth for the euro area V Aprigliano, C Foroni, M Marcellino, G Mazzi, F Venditti International Journal of Computational Economics and Econometrics 7 (1-2), 43-63, 2017 | 15 | 2017 |
A comparison of mixed frequency approaches for modelling euro area macroeconomic variables C Foroni, M Marcellino | 15 | 2012 |