Forecasting private consumption with Google Trends data
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DOI: 10.1002/for.2559
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Citations
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Cited by:
- Tihana Škrinjarić, 2019. "Time Varying Spillovers between the Online Search Volume and Stock Returns: Case of CESEE Markets," IJFS, MDPI, vol. 7(4), pages 1-30, October.
- Zhongchen Song & Tom Coupé, 2023.
"Predicting Chinese consumption series with Baidu,"
Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 21(3), pages 429-463, July.
- Zhongchen Song & Tom Coupé, 2022. "Predicting Chinese consumption series with Baidu," Working Papers in Economics 22/19, University of Canterbury, Department of Economics and Finance.
- Rodrigo Mulero & Alfredo García-Hiernaux, 2021. "Forecasting Spanish unemployment with Google Trends and dimension reduction techniques," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 12(3), pages 329-349, September.
- Jiam Song & Kwangmin Jung & Jonghun Kam, 2023. "Evidence of the time-varying impacts of the COVID-19 pandemic on online search activities relating to shopping products in South Korea," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-12, December.
- David Kohns & Arnab Bhattacharjee, 2020.
"Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model,"
Papers
2011.00938, arXiv.org, revised May 2022.
- Bhattacharjee, Arnab & Kohns, David, 2022. "Nowcasting Growth using Google Trends Data: A Bayesian Structural Time Series Model," National Institute of Economic and Social Research (NIESR) Discussion Papers 538, National Institute of Economic and Social Research.
- Vera Z. Eichenauer & Ronald Indergand & Isabel Z. Martínez & Christoph Sax, 2022. "Obtaining consistent time series from Google Trends," Economic Inquiry, Western Economic Association International, vol. 60(2), pages 694-705, April.
- Fu, Chun & Miller, Clayton, 2022. "Using Google Trends as a proxy for occupant behavior to predict building energy consumption," Applied Energy, Elsevier, vol. 310(C).
- Karaman Örsal, Deniz Dilan, 2021. "Onlinedaten und Konsumentscheidungen: Voraussagen anhand von Daten aus Social Media und Suchmaschinen," Edition HWWI: Chapters, in: Straubhaar, Thomas (ed.), Neuvermessung der Datenökonomie, volume 6, pages 157-172, Hamburg Institute of International Economics (HWWI).
- Kohns, David & Bhattacharjee, Arnab, 2023. "Nowcasting growth using Google Trends data: A Bayesian Structural Time Series model," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1384-1412.
- Fajar, Muhammad & Prasetyo, Octavia Rizky & Nonalisa, Septiarida & Wahyudi, Wahyudi, 2020. "Forecasting unemployment rate in the time of COVID-19 pandemic using Google trends data (case of Indonesia)," MPRA Paper 105042, University Library of Munich, Germany, revised 30 Nov 2020.
- Diaz-Balteiro, L. & Alfranca, O. & Voces, R. & Soliño, M., 2023. "Using google search patterns to explain the demand for wild edible mushrooms," Forest Policy and Economics, Elsevier, vol. 152(C).
- Rik Chakraborti & Gavin Roberts, 2020. "Anti-Gouging Laws, Shortages, and COVID-19: Insights from Consumer Searches," Journal of Private Enterprise, The Association of Private Enterprise Education, vol. 35(Winter 20), pages 1-20.
- Di Wu & Zhenning Xu & Seung Bach, 2023. "Using Google Trends to predict and forecast avocado sales," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(4), pages 629-641, December.
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