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Sparse Warcasting, by Mihnea Constantinescu

Author: Mihnea Constantinescu (National Bank of Ukraine, University of Amsterdam)

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.

Cite as: Constantinescu, M. (2023). Sparse Warcasting. NBU Working Papers, 1/2023. Kyiv: National Bank of Ukraine. Retrieved from

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Sparse Warcasting, by Mihnea Constantinescu
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