Nowcasting World Trade with Machine Learning: a Three-Step Approach
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Abstract
Suggested Citation
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Other versions of this item:
- Chinn, Menzie D. & Meunier, Baptiste & Stumpner, Sebastian, 2023. "Nowcasting world trade with machine learning: a three-step approach," Working Paper Series 2836, European Central Bank.
- Menzie D. Chinn & Baptiste Meunier & Sebastian Stumpner, 2023. "Nowcasting World Trade with Machine Learning: a Three-Step Approach," NBER Working Papers 31419, National Bureau of Economic Research, Inc.
Citations
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Cited by:
- Richard Schnorrenberger & Aishameriane Schmidt & Guilherme Valle Moura, 2024. "Harnessing Machine Learning for Real-Time Inflation Nowcasting," Working Papers 806, DNB.
- Donato Ceci & Orest Prifti & Andrea Silvestrini, 2024. "Nowcasting Italian GDP growth: a Factor MIDAS approach," Temi di discussione (Economic working papers) 1446, Bank of Italy, Economic Research and International Relations Area.
- Jean-Charles Bricongne & Baptiste Meunier & Raquel Caldeira, 2024. "Should Central Banks Care About Text Mining? A Literature Review," Working papers 950, Banque de France.
More about this item
Keywords
Forecasting; Big Data; Large Dataset; Factor Model; Pre-Selection;All these keywords.
JEL classification:
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
- E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
NEP fields
This paper has been announced in the following NEP Reports:- NEP-BIG-2023-08-14 (Big Data)
- NEP-FOR-2023-08-14 (Forecasting)
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