Sparse Warcasting

Mihnea Constantinescu ()
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Mihnea Constantinescu: National Bank of Ukraine

No 01/2023, Working Papers from National Bank of Ukraine

Abstract: Forecasting economic activity during an invasion is a nontrivial exercise. The lack of timely statistical data and the expected nonlinear effect of military action challenge the use of established nowcasting and short-term forecasting methodologies. This study explores the use of Partial Least Squares (PLS) augmented with an additional sparsity step to nowcast quarterly Ukrainian GDP using Google search data. Model outputs are benchmarked against both static and dynamic factor models. Preliminary results outline the usefulness of PLS in capturing the effects of large shocks in a setting rich in data, but poor in statistics.

Keywords: nowcasting; quarterly GDP; Google Trends; machine learning; partial; least squares; sparsity; Markov blanket (search for similar items in EconPapers)
JEL-codes: C38 C53 C55 E32 E37 (search for similar items in EconPapers)
Pages: 31 pages
Date: 2023-06
New Economics Papers: this item is included in nep-big, nep-cis and nep-tra
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Persistent link: https://EconPapers.repec.org/RePEc:ukb:wpaper:01/2023

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