Nowcasting Real GDP Growth in The Bahamas

José Luis Saboin, Diego Guerrero and Angelo Mazzocca

No 14635, IDB Publications (Working Papers) from Inter-American Development Bank

Abstract: This paper introduces a novel real GDP growth nowcasting strategy based on a distribution of nowcast values derived from a large dataset and multiple variable combinations, specifications and estimators. We exploit structured and unstructured data from The Bahamas, using thirteen estimators from the econometrics and machine learning literature. The study begins describing our dataset with over three hundred variables from the national statistics system, satellite nighttime lights data for key geographic locations in the archipelago, and internet search trends. Next, we nowcast the seasonally-adjusted annualized quarter-on-quarter growth rate of real gross domestic product using multiple combinations of variables, specifications and estimators. Overall, the ensemble method produces a distribution of nowcasts that outperform a human-designed benchmark. This paper contributes a novel idea of exploiting a distribution of estimates rather than point-values from a determined specification or estimator.

Keywords: Nowcasting; Tourism; machine learning; Time Series; Google Trends; nighttime lights; GDP Growth (search for similar items in EconPapers)
JEL-codes: C38 C53 C55 E37 L83 O47 O54 (search for similar items in EconPapers)
Date: 2026-05
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Persistent link: https://EconPapers.repec.org/RePEc:idb:brikps:14635

DOI: 10.18235/0014052

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