New Approaches to Forecasting Growth and Inflation: Big Data and Machine Learning
Amaani Bashir and
Mayank Jain ()
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Mayank Jain: Institute of Economic Growth, Delhi
No 446, IEG Working Papers from Institute of Economic Growth
The use of big data and machine learning techniques is now very common in many spheres and there is growing popularity of these approaches in macroeconomic forecasting as well. Is big data and machine learning really useful in the prediction of macroeconomic outcomes? Are they superior in performance compared to their traditional counterparts? What are the tradeoffs that forecasters need to keep in mind, and what are the steps they need to take to use these resources effectively? We carry out a critical analysis of the existing literature in order to answer these questions. Our analysis suggests that the answer to most of these questions are nuanced, conditional on a number of factors identified in the study.
Keywords: Forecasting; Big Data; Machine Learning; Supervised Learning; Meta-analysis; Growth; Inflation (search for similar items in EconPapers)
JEL-codes: C14 C45 C52 C53 C55 E17 E37 (search for similar items in EconPapers)
Pages: 43 pages
New Economics Papers: this item is included in nep-big, nep-cmp, nep-for and nep-mac
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Published as Institute of Economic Growth, Delhi, October 2021, pages 1-43
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Persistent link: https://EconPapers.repec.org/RePEc:awe:wpaper:446
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