SHORT-TERM FORECASTING OF SLOVAK GDP BASED ON HIGH-FREQUENCY DATA

PETER LÖRINC

https://doi.org/10.53465/ER.2644-7185.2025.2.132-163

Abstract: The paper compares two forecasts of Slovak GDP, the first with high-frequency data and the second without them. We utilize the last observation from the economic activity index acting as a short-term GDP forecast. We use data from 2000 to 2024 in weekly frequencies and have 27 variables related to different sectors such as: real activity, energy, households, labour, expectations, transport, financial data. We address the problem of Nowcasting of the growth rate of Slovak real GDP using dynamic factor models by incorporating ragged edges in the data. The outcome of the paper is that the model without high-frequency data has better forecasting capabilities and may better forecast economic recessions and growths in the Slovak Republic.

Keywords: Nowcasting, GDP, economic activity index, Kalman filter

JEL Classification: C53, E37, E01

Fulltext: PDF

Online publication date: 25 June 2025

To cite this article (APA style):

Lörinc, P. (2025). Short-term forecasting of Slovak GDP based on high-frequency data. Economic Review, 54(2), 132 ─ 163. https://doi.org/10.53465/ER.2644-7185.2025.2.132-163

Publisher: Bratislava University of Economics and Business

ISSN 2644-7185 (online)

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.