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Indikatoren zur Prognose der Investitionen in Deutschland
Döpke, Jörg; Fritsche, Ulrich; Gottschalk, Jan; … - 1999
In diesem Papier werden eine Reihe von Frühindikatoren für die Entwicklung der Ausrüstungs-, Wirtschaftsbau- und Wohnungsbauinvestitionen in Deutschland untersucht. Die Indikatoren werden auf Basis theoretischer Erwägungen oder wegen ihres technischen Zusammenhangs zur Investitionstätigkeit...
Persistent link: https://www.econbiz.de/10011495601
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U-MIDAS: MIDAS regressions with unrestricted lag polynomials
Foroni, Claudia; Marcellino, Massimiliano; Schumacher, … - Deutsche Bundesbank - 2011
Mixed-data sampling (MIDAS) regressions allow to estimate dynamic equations that explain a low-frequency variable by high-frequency variables and their lags. When the difference in sampling frequencies between the regressand and the regressors is large, distributed lag functions are typically...
Persistent link: https://www.econbiz.de/10009493254
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MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the Euro Area
Kuzin, Vladimir; Marcellino, Massimiliano; Schumacher, … - C.E.P.R. Discussion Papers - 2009
This paper compares the mixed-data sampling (MIDAS) and mixed-frequency VAR (MF-VAR) approaches to model specification in the presence of mixed-frequency data, e.g., monthly and quarterly series. MIDAS leads to parsimonious models based on exponential lag polynomials for the coefficients,...
Persistent link: https://www.econbiz.de/10008528546
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Pooling versus model selection for nowcasting with many predictors: An application to German GDP
Kuzin, Vladimir; Marcellino, Massimiliano; Schumacher, … - C.E.P.R. Discussion Papers - 2009
, amongst others, the factor estimation method and the number of factors, lag length and indicator selection. Thus, there are …
Persistent link: https://www.econbiz.de/10005123534
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Factor-MIDAS for now- and forecasting with ragged-edge data: A model comparison for German GDP
Marcellino, Massimiliano; Schumacher, Christian - C.E.P.R. Discussion Papers - 2008
combinations of factor estimation methods and Factor-MIDAS projections with respect to nowcast performance. Additionally, we …. Our empirical findings show that the factor estimation methods don't differ much with respect to nowcasting accuracy …
Persistent link: https://www.econbiz.de/10005124208
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Forecasting with Factor Models Estimated on Large Datasets: A Review of the Recent Literature and Evidence for German GDP
Schumacher, Christian - In: Journal of Economics and Statistics (Jahrbuecher fuer … 231 (2011) 1, pp. 28-49
estimation techniques are necessary, expanding on the standard approaches for balanced data such as principal components (PC …). The estimation methods include variants of the Expectation-Maximisation (EM) algorithm together with PC and factor … estimation using state-space models. Given the estimated factors, forecasts can be obtained from bridge equations, mixed …
Persistent link: https://www.econbiz.de/10008854422
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MIDAS and bridge equations
Schumacher, Christian - Deutsche Bundesbank - 2014
This paper compares two single-equation approaches from the recent nowcast literature: Mixed-data sampling (MIDAS) regressions and bridge equations. Both approach are used to nowcast a low-frequency variable such as quarterly GDP growth by higher-frequency business cycle indicators. Three...
Persistent link: https://www.econbiz.de/10011093850
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MIDAS regressions with time-varying parameters: An application to corporate bond spreads and GDP in the Euro area
Schumacher, Christian - Verein für Socialpolitik - VfS - 2014
the estimation approach. A real-time application to the relationship between daily corporate bond spreads and quarterly …
Persistent link: https://www.econbiz.de/10011164090
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U-MIDAS: MIDAS regressions with unrestricted lag polynomials
Foroni, Claudia; Marcellino, Massimiliano; Schumacher, … - C.E.P.R. Discussion Papers - 2012
Mixed-data sampling (MIDAS) regressions allow to estimate dynamic equations that explain a low-frequency variable by high-frequency variables and their lags. When the difference in sampling frequencies between the regressand and the regressors is large, distributed lag functions are typically...
Persistent link: https://www.econbiz.de/10011084496
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Real-time forecasting of GDP based on a large factor model with monthly and quarterly data
Schumacher, Christian; Breitung, Jörg - 2006
Persistent link: https://www.econbiz.de/10003389580