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A Machine Learning Approach to Constructing Weekly GDP Tracker Using Google Trends

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A Machine Learning Approach to Constructing Weekly GDP Tracker Using Google Trends

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Armas, JC.; R. Mapa, C.; T. Guliman, MEJ.; G. Castañares, ML.; S. Centeno, GP. (2023). A Machine Learning Approach to Constructing Weekly GDP Tracker Using Google Trends. Editorial Universitat Politècnica de València. 55-62. https://doi.org/10.4995/CARMA2023.2023.16039

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/201694

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Title: A Machine Learning Approach to Constructing Weekly GDP Tracker Using Google Trends
Author: Armas, Jean Christine R. Mapa, Cherrie T. Guliman, Ma. Ellysah Joy G. Castañares, Michael Lawrence S. Centeno, Genna Paola
Issued date:
Abstract:
[EN] The outbreak of the COVID-19 pandemic further highlighted the limitation of existing traditional indicators as policy formulation, particularly during crisis periods, demands timely and granular data. We construct the ...[+]
Subjects: Nowcasting , GDP , Google Trends , Machine learning models , Neural networks
Copyrigths: Reconocimiento - No comercial - Compartir igual (by-nc-sa)
ISBN: 9788413960869
Source:
5th International Conference on Advanced Research Methods and Analytics (CARMA 2023).
DOI: 10.4995/CARMA2023.2023.16039
Publisher:
Editorial Universitat Politècnica de València
Publisher version: http://ocs.editorial.upv.es/index.php/CARMA/CARMA2023/paper/view/16039
Conference name: CARMA 2023 - 5th International Conference on Advanced Research Methods and Analytics
Conference place: Sevilla, España
Conference date: Junio 28-30, 2023
Type: Capítulo de libro Comunicación en congreso

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