Andrii Babii, Luca Barbaglia, Eric Ghysels, Jonas Striaukas
arXiv 29 Sep 2025 · Econometrics
arXiv:2509.24780 · PDF · DOI · OpenAlex · Extracted main text
The paper studies the nowcasting of Euro area Gross Domestic Product (GDP) growth using mixed data sampling machine learning panel data regressions with both standard macro releases and daily news data. Using a panel of 19 Euro area countries, we investigate whether directly nowcasting the Euro area aggregate is better than weighted individual country nowcasts. Our results highlight the importance of the information from small- and medium-sized countries, particularly when including the COVID-19 pandemic period. The empirical analysis is supplemented by studying the so-called Big Four -- France, Germany, Italy, and Spain -- and the value added of news data when official statistics are lagging. From a theoretical perspective, we formally show that the aggregation of individual components forecasted with pooled panel data regressions is superior to direct aggregate forecasting due to lower estimation error.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Babii, Ghysels, and Striaukas (2022) Machine learning time series regressions with an application to nowcasting self | 1.000 | 13 | 3 | 100% |
| 2 | Babii, Ball, Ghysels, and Striaukas (2023) Machine learning panel data regressions with heavy-tailed dependent data: Theory and application | 1.000 | 8 | 4 | 100% |
| 3 | Babii, Ball, Ghysels, and Striaukas (2024) Panel Data Nowcasting in a Data-Rich Environment: The Case of Price-Earnings Ratios | 0.928 | 4 | 3 | 100% |
| 4 | Ashwin, Kalamara, and Saiz (2024) Nowcasting Euro area GDP with news sentiment: A tale of two crises | 0.843 | 3 | 3 | 100% |
| 5 | Cascaldi-Garcia, Ferreira, Giannone, and Modugno (2023) Back to the present: Learning about the euro area through a now-casting model | 0.843 | 3 | 3 | 100% |
| 6 | Barbaglia, Consoli, and Manzan (2024) Forecasting GDP in Europe with textual data | 0.737 | 3 | 2 | 100% |
| 7 | Consoli, Barbaglia, and Manzan (2022) Fine-grained, aspect-based sentiment analysis on economic and financial lexicon | 0.737 | 3 | 2 | 100% |
| 8 | Boss, Longo, and Onorante (2025) Nowcasting the euro area with social media data | 0.644 | 2 | 2 | 100% |
| 9 | Quaedvlieg (2021) Multi-horizon forecast comparison | 0.585 | 3 | 1 | 100% |
| 10 | Schorfheide and Song (2015) Real-time forecasting with a mixed-frequency VAR | 0.585 | 3 | 1 | 100% |
Showing the top 10 of 37 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Nowcasting distributions: a functional MIDAS model | 0.405 | 1 | 1 |