The D-model for GDP nowcasting

Stavros Degiannakis

Swiss Journal of Economics and Statistics, 2023, vol. 159, issue 1, 1-33

Abstract: Abstract The paper provides a disaggregated mixed-frequency framework for the estimation of GDP. The GDP is disaggregated into components that can be forecasted based on information available at higher sampling frequency, i.e., monthly, weekly, or daily. The model framework is applied for Greek GDP nowcasting. The results provide evidence that the more accurate nowcasting estimations require (i) the disaggregation of GDP, (ii) the use of a multilayer mixed-frequency framework, and (iii) the inclusion of financial information on a daily frequency. The simulation study provides evidence in favor of the disaggregation into components despite the inclusion of multiple sources of forecast errors.

Keywords: Nowcasting; Forecasting; GDP; Disaggregation; Factors; Multilayer; Mixed frequency (search for similar items in EconPapers)
JEL-codes: C53 E27 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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Working Paper: The D-model for GDP nowcasting (2023)
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DOI: 10.1186/s41937-023-00109-8

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