Predicting the Present Revisited: The Case of Thailand
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- 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.
- Tanya Suhoy, 2009. "Query Indices and a 2008 Downturn: Israeli Data," Bank of Israel Working Papers 2009.06, Bank of Israel.
- Nuarpear Lekfuangfu & Voraprapa Nakavachara & Paphatsorn Sawaengsuksant, 2017. "Glancing at Labour Market Mismatch with User-generated Internet Data," PIER Discussion Papers 53, Puey Ungphakorn Institute for Economic Research.
- 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.
- Omer ZEYBEK & Erginbay UGURLU, 2014. "Nowcasting Credit Demand in Turkey with Google Trends Data," International Conference on Economic Sciences and Business Administration, Spiru Haret University, vol. 1(1), pages 333-340, December.
- McLaren, Nick & Shanbhogue, Rachana, 2011. "Using internet search data as economic indicators," Bank of England Quarterly Bulletin, Bank of England, vol. 51(2), pages 134-140.
- Steven Berry & James Levinsohn & Ariel Pakes, 2004.
"Differentiated Products Demand Systems from a Combination of Micro and Macro Data: The New Car Market,"
Journal of Political Economy, University of Chicago Press, vol. 112(1), pages 68-105, February.
- Steven Berry & James Levinsohn & Ariel Pakes, 1998. "Differentiated Products Demand Systems from a Combination of Micro and Macro Data: The New Car Market," NBER Working Papers 6481, National Bureau of Economic Research, Inc.
- Levinsohn, James & Berry, Steven & Pakes, Ariel, 2004. "Differentiated Products Demand Systems from a Combination of Micro and Macro Data: The New Car Market," Scholarly Articles 3436404, Harvard University Department of Economics.
- Steven Berry & James Levinsohn & Ariel Pakes, 2001. "Differentiated Products Demand Systems from a Combination of Micro and Macro Data: The New Car Market," Cowles Foundation Discussion Papers 1337, Cowles Foundation for Research in Economics, Yale University.
- Hyunyoung Choi & Hal Varian, 2012. "Predicting the Present with Google Trends," The Economic Record, The Economic Society of Australia, vol. 88(s1), pages 2-9, June.
- Seabold,Skipper & Coppola,Andrea, 2015. "Nowcasting prices using Google trends : an application to Central America," Policy Research Working Paper Series 7398, The World Bank.
- Vicente, María Rosalía & López-Menéndez, Ana J. & Pérez, Rigoberto, 2015. "Forecasting unemployment with internet search data: Does it help to improve predictions when job destruction is skyrocketing?," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 132-139.
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More about this item
Keywords
Nowcasting; Google Trends;JEL classification:
- J01 - Labor and Demographic Economics - - General - - - Labor Economics: General
- L62 - Industrial Organization - - Industry Studies: Manufacturing - - - Automobiles; Other Transportation Equipment; Related Parts and Equipment
- G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
- G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
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