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Forecasting Inflation with Gradual Regime Shifts and Exogenous Information
Hubrich, Kirstin - 2011
We propose a new method for medium-term forecasting using exogenous information. We first show how a shifting … for estimating the model parameters. In forecasting inflation, the central bank inflation target, if it exists, is a … natural example of such exogenous information. We illustrate the application of our method by an out-of-sample forecasting …
Persistent link: https://www.econbiz.de/10013122536
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Estimation of Impulse Response Functions When Shocks are Observed at a Higher Frequency than Outcome Variables
Chudik, Alexander; Georgiadis, Georgios - 2021
This paper proposes mixed-frequency distributed-lag (MFDL) estimators of impulse response functions (IRFs) in a setup where (i) the shock of interest is observed, (ii) the impact variable of interest is observed at a lower frequency (as a temporally aggregated or sequentially sampled variable),...
Persistent link: https://www.econbiz.de/10013315353
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Is Forecasting with Large Models Informative? Assessing the Role of Judgement in Macroeconomic Forecasts
Mestre, Ricardo; McAdam, Peter - 2021
a significant impact of forecasting accuracy irrespective of the model in use, ostensibly due to the presence of breaks …
Persistent link: https://www.econbiz.de/10013316469
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Detecting and Predicting Forecast Breakdowns
Giacomini, Raffaella; Rossi, Barbara - 2021
We propose a theoretical framework for assessing whether a forecast model estimated over one period can provide good forecasts over a subsequent period. We formalize this idea by defining a forecast breakdown as a situation in which the out-of-sample performance of the model, judged by some loss...
Persistent link: https://www.econbiz.de/10013317583
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Is forecasting with large models informative? Assessing the role of judgement in macroeconomic forecasts
Mestre, Ricardo; McAdam, Peter - 2008
a significant impact of forecasting accuracy irrespective of the model in use, ostensibly due to the presence of breaks …
Persistent link: https://www.econbiz.de/10011604996
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On Approximating DSGE Models by Series Expansions
Lombardo, Giovanni - 2010
We show how to use a simple perturbation method to solve non-linear rational expectation models. Drawing from the applied mathematics literature we propose a method consisting of series expansions of the non-linear system around a known solution. The variables are represented in terms of their...
Persistent link: https://www.econbiz.de/10013136525
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Statistical Tests and Estimators of the Rank of a Matrix and their Applications in Econometric Modelling
Camba-Mendez, Gonzalo; Kapetanios, George - 2021
Testing and estimating the rank of a matrix of estimated parameters is key in a large variety of econometric modelling scenarios. This paper describes general methods to test for and estimate the rank of a matrix, and provides details on a variety of modelling scenarios in the econometrics...
Persistent link: https://www.econbiz.de/10013316643
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Trend-Cycle Decomposition of Output and Euro Area Inflation Forecasts : A Real-Time Approach Based on Model Combination
Guerin, Pierre - 2011
The paper focuses on the estimation of the euro area output gap. We construct model-averaged measures of the output gap …-time estimates to check the stability of the estimates to GDP revisions. We finally run a forecasting experiment to evaluate the … estimates in real time. Our measures help forecasting inflation over most of our evaluation sample (2001-2010) but fail …
Persistent link: https://www.econbiz.de/10013120226
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Forecasting Fiscal Time Series Using Mixed Frequency Data
Asimakopoulos, Stylianos - 2013
series at annual frequency. This makes the analysis useful in the typical forecasting environment of large institutions …
Persistent link: https://www.econbiz.de/10013082111
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Forecasting Daily Electricity Prices with Monthly Macroeconomic Variables
Foroni, Claudia - 2019
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 unrestricted MIDAS models (RU-MIDAS). We study the forecasting accuracy …
Persistent link: https://www.econbiz.de/10012890163