| 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 | 368 | 2015 |
| A survey of econometric methods for mixed-frequency data C Foroni, MG Marcellino Available at SSRN 2268912, 2013 | 240 | 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 | 166 | 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 | 114 | 2022 |
| Labor supply factors and economic fluctuations C Foroni, F Furlanetto, A Lepetit International Economic Review 59 (3), 1491-1510, 2018 | 94 | 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 | 90 | 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 | 73 | 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 |
| Mixed‐frequency structural models: Identification, estimation, and policy analysis C Foroni, M Marcellino Journal of Applied Econometrics 29 (7), 1118-1144, 2014 | 46 | 2014 |
| Density forecasts with MIDAS models KA Aastveit, C Foroni, F Ravazzolo Journal of Applied Econometrics 32 (4), 783-801, 2017 | 43 | 2017 |
| Markov-switching mixed-frequency VAR models C Foroni, P Guérin, M Marcellino International Journal of Forecasting 31 (3), 692-711, 2015 | 42 | 2015 |
| U-MIDAS: MIDAS regressions with unrestricted lag polynomials C Foroni, MG Marcellino, C Schumacher Bundesbank Series 1 Discussion Paper, 2011 | 42 | 2011 |
| 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 | 35 | 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 | 32 | 2016 |
| Uncertainty through the lenses of a mixed-frequency Bayesian panel Markov-switching model R Casarin, C Foroni, M Marcellino, F Ravazzolo | 24 | 2018 |
| Mixed‐frequency models with moving‐average components C Foroni, M Marcellino, D Stevanovic Journal of Applied Econometrics 34 (5), 688-706, 2019 | 21 | 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 | 17 | 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 | 16 | 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 | 16 | 2017 |
| A comparison of mixed frequency approaches for modelling euro area macroeconomic variables C Foroni, M Marcellino | 14 | 2012 |
