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Forecasting Quarterly German GDP at Monthly Intervals Using Monthly Ifo Business Conditions Data
Mittnik, Stefan; Zadrozny, Peter A. - 2021
Kalman-filtering-based maximum-likelihood estimation method. Following the method, we estimate monthly and quarterly VAR(2 … GDP forecasts. The Kalman filter is used to compute the likelihood in estimation and to produce forecasts. Generally, the …
Persistent link: https://www.econbiz.de/10013319236
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Forecasting quarterly German GDP at monthly intervals using monthly IFO business conditions data
Mittnik, Stefan; Zadrozny, Peter A. - 2004
Kalman-filtering-based maximum-likelihood estimation method. Following the method, we estimate monthly and quarterly VAR(2 … GDP forecasts. The Kalman filter is used to compute the likelihood in estimation and to produce forecasts. Generally, the …
Persistent link: https://www.econbiz.de/10010277284
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Forecasting quaterly German GDP at mothly intervals using monthly ifo business conditions data
Mittnik, Stefan; Zadrozny, Peter A. - In: Ifo survey data in business cycle and monetary policy …, (pp. 19-48). 2004
Persistent link: https://www.econbiz.de/10002391298
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Forecasting quarterly German GDP at monthly intervals using monthly IFO business conditions data : presented at CESifo conference "Academic Use of ifo Survey Data", december 2003
Mittnik, Stefan; Zadrozny, Peter A. - 2004
Kalman-filtering-based maximum-likelihood estimation method. Following the method, we estimate monthly and quarterly VAR(2 … GDP forecasts. The Kalman filter is used to compute the likelihood in estimation and to produce forecasts. Generally, the …
Persistent link: https://www.econbiz.de/10002104553
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Heuristic model selection for leading indicators in Russia and Germany
Savin, Ivan; Winker, Peter - 2011
leading indicator property is assessed with regard to forecasting industrial production in Russia and Germany. For this … forecasting performance of the leading indicators for both countries revealing marked differences between Russia and Germany …
Persistent link: https://www.econbiz.de/10008807367
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Forecasting German key macroeconomic variables using large dataset methods
Pirschel, Inske; Wolters, Maik H. - 2014
We study the forecasting performance of three alternative large scale approaches using a dataset for Germany that … vector autoregression and model averaging techniques, where aggregation takes place before, during and after the estimation …
Persistent link: https://www.econbiz.de/10010357899
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Forecasting German key macroeconomic variables using large dataset methods : conference paper
Pirschel, Inske; Wolters, Maik H. - 2014
estimation of the different models, respectively. We find that overall the large Bayesian VAR provides the most precise forecasts …
Persistent link: https://www.econbiz.de/10010489849
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Should forecasters use real-time data to evaluate leading indicator models for GDP prediction? : German evidence
Heinisch, Katja; Scheufele, Rolf - 2017
relative to industrial production and orders in Germany. Although we find evidence that forecast characteristics based on real …
Persistent link: https://www.econbiz.de/10011595370
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Bayesian Compression for Mixed Frequency Vector Autoregressions : A Forecast Study for Germany
Götz, Thomas - 2018
Up until now, the concept of compression in single- or multivariate regressions has been limited to the common-frequency case. Having an application of macroeconomic forecasting in mind, one inevitably has to deal with variables sampled at various frequencies. Consequently, this work attempts to...
Persistent link: https://www.econbiz.de/10012912645
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Assessing the macroeconomic forecasting performance of boosting : evidence for the United States, the Euro Area, and Germany
Buchen, Teresa; Wohlrabe, Klaus - 2013
to the fit. Using data for the United States, the euro area and Germany, we assess the performance of boosting when …
Persistent link: https://www.econbiz.de/10009721997