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Tracking economic activity with alternative high-frequency data

Eckert, Florian; Kronenberg, Philipp; Mikosch, Heiner; … - 2020

Most macroeconomic indicators failed to capture the sharp economic fluctuations during the Corona crisis in a timely manner. Instead, alternative high-frequency data have been used, aiming to monitor the economic situation. However, these data are often only loosely related to the business cycle...

Persistent link: https://www.econbiz.de/10012395297

Data Revisions and Real-Time Probabilistic Forecasting of Macroeconomic Variables

Clements, Michael P. - 2017

real-time out-of-sample forecasts from models effectively makes no allowance for this form of data uncertainty. We analyse … a simple method which has been used in the context of point forecasting, and does make an allowance for data uncertainty … to improve real-time density forecasts. We show that the magnitude of the improvements that might be achieved from this …

Persistent link: https://www.econbiz.de/10012951549

Macroeconomics, nonlinearities, and the business cycle

Reif, Magnus - 2019

Im Zentrum dieser Dissertation steht das Beschreiben und Erklären von Konjunkturdynamiken. Motiviert durch den außerordentlich starken wirtschaftlichen Einbruch in 2008/2009 betont die Arbeit dabei die Wichtigkeit der Nutzung von nichtlinearen Modellansätzen. Die Dissertation kann als Beitrag...

Persistent link: https://www.econbiz.de/10012154125

MIDAS versus mixed-frequency VAR : nowcasting GDP in the euro area

Kuzin, Vladimir; Marcellino, Massimiliano; Schumacher, … - 2009

This paper compares the mixed-data sampling (MIDAS) and mixed-frequency VAR (MF-VAR) approaches to model speci.cation 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 coeØ cients, whereas...

Persistent link: https://www.econbiz.de/10003815492

Robust implementation of a parsimonious dynamic factor model to nowcast GDP

Duarte, Pablo; Süssmuth, Bernd - 2014

Quarterly GDP figures usually are published with a delay of some weeks. A common way to generate GDP series of higher frequency, i.e. to nowcast GDP, is to use available indicators to calculate a single index by means of a common factor derived from a dynamic factor model (DFM). This paper deals...

Persistent link: https://www.econbiz.de/10010229863

Midas Versus Mixed-Frequency VAR : Nowcasting GDP in the Euro Area

Kuzin, Vladimir - 2016

This paper compares the mixed-data sampling (MIDAS) and mixed-frequency VAR (MF-VAR) approaches to model speci…cation 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 coe¢ cients,...

Persistent link: https://www.econbiz.de/10012991063

Regime-dependent nowcasting of the Austrian economy

Fortin, Ines; Hlouskova, Jaroslava - 2023

We nowcast and forecast Austrian economic activity, namely real gross domestic product (GDP), consumption and … autoregressive model according to Ghysels (2016) and mixed data sampling approaches, and compare their forecast and nowcast …/economic uncertainty regimes (high/low uncertainty) driven by global and Austrian economic and financial uncertainty indicators. We find …

Persistent link: https://www.econbiz.de/10014432187