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Submitted
January 6, 2023
Accepted
January 20, 2023
Published
January 27, 2023
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Abstract

This research aims to assess the possibility of the daily and weekly Google Trends Index (GTI) to predict the quarterly GDP growth. The U-MIDAS approach is utilized because it allows using of daily and weekly basis data to forecast quarterly indicators without aggregating them onto a quarterly basis hence it does not eliminate useful information on the daily and weekly data. This research uses quarterly GDP for the transportation sector and the accommodation and restaurant sector which are considered potential industries for the future of Indonesia's economy. The result shows that the daily basis GTI can effectively predict the quarterly GDP growth better than the weekly basis GTI based on the RSE scores.

Keywords

alternative data big data GDP mixed frequency data MIDAS

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Author Biography

Nucke Widowati Kusumo Projo, Politeknik Statistika STIS, Jl. Otto Iskandardinata No. 64 C, Jakarta Timur 13330

Plh. Kepala Unit Penelitian Statistik Sosial dan Ekonomi, Politeknik Statistika STIS

How to Cite
Larasati, D. N. ., & Projo, N. W. K. (2023). Nowcasting the Transportation and Accommodation Sectors Growth using the Google Trends Index. EKSAKTA: Journal of Sciences and Data Analysis, 4(1), 29–39. https://doi.org/10.20885/EKSAKTA.vol4.iss1.art4
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