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Forecasting daily electricity prices with monthly macroeconomic variables
Foroni, Claudia; Ravazzolo, Francesco; Rossini, Luca - 2019
We analyse the importance of macroeconomic information, such as industrial production index and oil price, for forecasting daily electricity prices in two of the main European markets, Germany and Italy. We do that by means of mixed-frequency models, introducing a Bayesian approach to reverse...
Persistent link: https://www.econbiz.de/10011987142
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Forecasting euro area inflation : does aggregating forecasts by HICP component improve forecast accuracy?
Hubrich, Kirstin (contributor) - 2003
Persistent link: https://www.econbiz.de/10001820871
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Trend-cycle decomposition of output and euro area inflation forecasts : a real-time approach based on model combination
Guérin, Pierre; Maurin, Laurent; Mohr, Matthias - 2011
; Markov-switching ; Auxiliary information ; Model averaging ; Inflation forecast ; Real-time analysis …
Persistent link: https://www.econbiz.de/10009380402
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Weigh(t)ing the basket : aggregate and component-based inflation forecasts for the euro area
Chalmovianský, Jakub; Porqueddu, Mario; Sokol, Andrej - 2020
We compare direct forecasts of HICP and HICP excluding energy and food in the euro area and five member countries to aggregated forecasts of their main components from large Bayesian VARs with a shared set of predictors. We focus on conditional point and density forecasts, in line with...
Persistent link: https://www.econbiz.de/10012384462
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Does the Phillips curve help to forecast euro area inflation?
Bańbura, Marta; Bobeica, Elena - 2020
breaks in the performance of most simple Phillips curves. Euro area inflation was particularly hard to forecast in the run … in a forecaster's toolkit. We base these conclusions on an extensive forecast evaluation over 1994 - 2018, an … estimated slack or by estimates from international economic institutions; (iii) external variables do not bring forecast gains …
Persistent link: https://www.econbiz.de/10012299084
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Merging structural and reduced-form models for forecasting : opening the DSGE-VAR box
Martínez-Martín, Jaime; Morris, Richard; Onorante, Luca; … - 2019
The post-crisis environment has posed important challenges to standard forecasting models. In this paper, we exploit several combinations of a large-scale DSGE structural model with standard reduced-form methods such as (B)VAR (i.e. DSGE-VAR and Augmented-(B)VARDSGE methods) and assess their use...
Persistent link: https://www.econbiz.de/10012132553
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On the design of data sets for forecasting with dynamic factor models
Rünstler, Gerhard - 2016
Persistent link: https://www.econbiz.de/10011618253
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An automatic leading indicator, variable reduction and variable selection methods using small and large datasets : forecasting the industrial production growth for euro area econom...
Camba-Méndez, Gonzalo; Kapetanios, George; Papailias, Fotis - 2015
Persistent link: https://www.econbiz.de/10010516546
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Price dividend ratio and long-run stock returns : a score driven state space model
Delle Monache, Davide; Petrella, Ivan; Venditti, Fabrizio - 2020
In this paper we develop a general framework to analyze state space models with timevarying system matrices where time variation is driven by the score of the conditional likelihood. We derive a new filter that allows for the simultaneous estimation of the state vector and of the time-varying...
Persistent link: https://www.econbiz.de/10012156426
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Inducing sparsity and shrinkage in time-varying parameter models
Huber, Florian; Koop, Gary; Onorante, Luca - 2019
TVP regressions. In a macroeconomic forecast exercise, we find our approach to substantially improve forecast performance …
Persistent link: https://www.econbiz.de/10012117683