Abstract
The interplay between maritime commerce and macroeconomic aggregates such as gross domestic product (GDP) and international trade statistics is key for the understanding of global economic dynamics. In this paper, we construct a new indicator, the Port Saturation Index, based on near-to-real-time port satellite images, which are processed with deep learning techniques to extract relevant information on the size of ongoing maritime commerce. We investigate the efficacy of the index with an empirical application to nowcast economic aggregates and forecast expansions and contractions of European GDP, import, and export. Results show that the index is able to closely track real economic activity, particularly GDP, when the figure is still far from its official release, yielding a novel tool for policy makers to support decision-making.
| Lingua originale | Inglese |
|---|---|
| pagine (da-a) | 463-496 |
| Numero di pagine | 34 |
| Rivista | Journal of the Royal Statistical Society. Series A: Statistics in Society |
| Numero di pubblicazione | 189(1) |
| DOI | |
| Stato di pubblicazione | Pubblicato - 2025 |
All Science Journal Classification (ASJC) codes
- Statistica e Probabilità
- Scienze Sociali (varie)
- Economia ed Econometria
- Statistica, Probabilità e Incertezza
Keywords
- Dynamic factor models
- Nowcasting
- Port containers
- Satellite images
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