Google's MIDAS Touch: Predicting UK Unemployment with Internet Search Data
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- Havranek, Tomas & Zeynalov, Ayaz, 2018. "Forecasting Tourist Arrivals with Google Trends and Mixed Frequency Data," EconStor Preprints 187420, ZBW - Leibniz Information Centre for Economics.
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- Havranek, Tomas & Zeynalov, Ayaz, 2018. "Forecasting Tourist Arrivals: Google Trends Meets Mixed Frequency Data," MPRA Paper 90205, University Library of Munich, Germany.
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- Coble, David & Pincheira, Pablo, 2017. "Nowcasting Building Permits with Google Trends," MPRA Paper 76514, University Library of Munich, Germany.
- Philip ME Garboden, 2019. "Sources and Types of Big Data for Macroeconomic Forecasting," Working Papers 2019-3, University of Hawaii Economic Research Organization, University of Hawaii at Manoa.
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- Johannes Bock, 2018. "Quantifying macroeconomic expectations in stock markets using Google Trends," Papers 1805.00268, arXiv.org.
- Chong, Terence Tai Leung & Wu, Zhang & Liu, Yuchen, 2019. "Market Reaction to iPhone Rumors," MPRA Paper 92014, University Library of Munich, Germany.
- Maas, Benedikt, 2019. "Short-term forecasting of the US unemployment rate," MPRA Paper 94066, University Library of Munich, Germany.
- María Gil & Javier J. Pérez & Alberto Urtasun, 2019.
"Nowcasting private consumption: traditional indicators, uncertainty measures, credit cards and some internet data,"
IFC Bulletins chapters,in: Bank for International Settlements (ed.), The use of big data analytics and artificial intelligence in central banking, volume 50
Bank for International Settlements.
- María Gil & Javier J. Pérez & A. Jesús Sánchez & Alberto Urtasun, 2018. "Nowcasting private consumption: traditional indicators, uncertainty measures, credit cards and some internet data," Working Papers 1842, Banco de España;Working Papers Homepage.
- repec:eee:intfor:v:35:y:2019:i:1:p:170-180 is not listed on IDEAS
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