Can Google Search Data Improve the Unemployment Rate Forecasting Model? An Empirical Analysis for Turkey
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DOI: 10.26650/JEPR963438
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- Jaroslav Pavlicek & Ladislav Kristoufek, 2015.
"Nowcasting Unemployment Rates with Google Searches: Evidence from the Visegrad Group Countries,"
PLOS ONE, Public Library of Science, vol. 10(5), pages 1-11, May.
- Pavlicek, Jaroslav & Kristoufek, Ladislav, 2015. "Nowcasting unemployment rates with Google searches: Evidence from the Visegrad Group countries," FinMaP-Working Papers 34, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
- Fondeur, Y. & Karamé, F., 2013.
"Can Google data help predict French youth unemployment?,"
Economic Modelling, Elsevier, vol. 30(C), pages 117-125.
- Frédéric Karamé & Yannick Fondeur, 2012. "Can Google Data Help Predict French Youth Unemployment?," Documents de recherche 12-03, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.
- Y. Fondeur & F. Karamé, 2013. "Can Google data help predict French youth unemployment?," Post-Print hal-02297071, HAL.
- Nikolaos Askitas & Klaus F. Zimmermann, 2009.
"Google Econometrics and Unemployment Forecasting,"
Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 55(2), pages 107-120.
- Nikos Askitas & Klaus F. Zimmermann, 2009. "Google Econometrics and Unemployment Forecasting," RatSWD Research Notes 41, German Data Forum (RatSWD).
- Askitas, Nikos & Zimmermann, Klaus F., 2009. "Google Econometrics and Unemployment Forecasting," IZA Discussion Papers 4201, Institute of Labor Economics (IZA).
- Nikos Askitas & Klaus F. Zimmermann, 2009. "Google Econometrics and Unemployment Forecasting," Discussion Papers of DIW Berlin 899, DIW Berlin, German Institute for Economic Research.
- Jain, Anshul & Biswal, Pratap Chandra, 2019. "Does internet search interest for gold move the gold spot, stock and exchange rate markets? A study from India," Resources Policy, Elsevier, vol. 61(C), pages 501-507.
- Aouadi, Amal & Arouri, Mohamed & Teulon, Frédéric, 2013. "Investor attention and stock market activity: Evidence from France," Economic Modelling, Elsevier, vol. 35(C), pages 674-681.
- Goddard, John & Kita, Arben & Wang, Qingwei, 2015. "Investor attention and FX market volatility," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 38(C), pages 79-96.
- Zhi Da & Joseph Engelberg & Pengjie Gao, 2011. "In Search of Attention," Journal of Finance, American Finance Association, vol. 66(5), pages 1461-1499, October.
- Mondria, Jordi & Wu, Thomas & Zhang, Yi, 2010.
"The determinants of international investment and attention allocation: Using internet search query data,"
Journal of International Economics, Elsevier, vol. 82(1), pages 85-95, September.
- Jordi Mondria & Thomas Wu & Yi Zhang, 2008. "The Determinants of International Investment and Attention Allocation: Using Internet Search Query Data," Working Papers tecipa-326, University of Toronto, Department of Economics.
- Nuno Barreira & Pedro Godinho & Paulo Melo, 2013. "Nowcasting unemployment rate and new car sales in south-western Europe with Google Trends," Netnomics, Springer, vol. 14(3), pages 129-165, November.
- Meltem Gulenay Chadwick & Gonul Sengul, 2015.
"Nowcasting the Unemployment Rate in Turkey : Let's ask Google,"
Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 15(3), pages 15-40.
- Meltem Gulenay Chadwick & Gonul Sengul, 2012. "Nowcasting Unemployment Rate in Turkey : Let's Ask Google," Working Papers 1218, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
- Smith, Geoffrey Peter, 2012. "Google Internet search activity and volatility prediction in the market for foreign currency," Finance Research Letters, Elsevier, vol. 9(2), pages 103-110.
- Bangwayo-Skeete, Prosper F. & Skeete, Ryan W., 2015. "Can Google data improve the forecasting performance of tourist arrivals? Mixed-data sampling approach," Tourism Management, Elsevier, vol. 46(C), pages 454-464.
- Eli Beracha & M. Babajide Wintoki, 2013. "Forecasting Residential Real Estate Price Changes from Online Search Activity," Journal of Real Estate Research, American Real Estate Society, vol. 35(3), pages 283-312.
- Melody Y. Huang & Randall R. Rojas & Patrick D. Convery, 2020. "Forecasting stock market movements using Google Trend searches," Empirical Economics, Springer, vol. 59(6), pages 2821-2839, December.
- Han, Liyan & Lv, Qiuna & Yin, Libo, 2017. "Can investor attention predict oil prices?," Energy Economics, Elsevier, vol. 66(C), pages 547-558.
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More about this item
Keywords
Google trends; Unemployment rate; Time-series model; Forecasting; ARIMA JEL Classification : C53 ; E24 ; E37;All these keywords.
JEL classification:
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
- E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
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