Comparing time series characteristics of official and web job vacancy data
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DOI: 10.1007/s11135-019-00940-3
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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, 2015.
"The internet as a data source for advancement in social sciences,"
International Journal of Manpower, Emerald Group Publishing Limited, vol. 36(1), pages 2-12, April.
- Nikolaos Askitas & Klaus F. Zimmermann, 2015. "The Internet as a Data Source for Advancement in Social Sciences," RatSWD Working Papers 248, German Data Forum (RatSWD).
- Askitas, Nikos & Zimmermann, Klaus F., 2015. "The Internet as a Data Source for Advancement in Social Sciences," IZA Discussion Papers 8899, Institute of Labor Economics (IZA).
- D'Amuri, Francesco & Marcucci, Juri, 2009.
"‘Google it!’ Forecasting the US unemployment rate with a Google job search index,"
ISER Working Paper Series
2009-32, Institute for Social and Economic Research.
- Francesco D’Amuri & Juri Marcucci, 2010. "“Google it!”Forecasting the US Unemployment Rate with a Google Job Search index," Working Papers 2010.31, Fondazione Eni Enrico Mattei.
- D'Amuri, Francesco/FD & Marcucci, Juri/JM, 2009. ""Google it!" Forecasting the US unemployment rate with a Google job search index," MPRA Paper 18248, University Library of Munich, Germany.
- Pietro Lovaglio & Mario Mezzanzanica, 2013. "Classification of longitudinal career paths," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(2), pages 989-1008, February.
- 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.
- Karolien Lenaerts & Miroslav Beblavý & Brian Fabo, 2016.
"Prospects for utilisation of non-vacancy Internet data in labour market analysis—an overview,"
IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 5(1), pages 1-18, December.
- Karolien Lenaerts & Miroslav Beblavý & Brian Fabo, 2016. "Prospects for utilisation of non-vacancy Internet data in labour market analysis—an overview," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 5(1), pages 1-18, December.
- Engle, Robert & Granger, Clive, 2015.
"Co-integration and error correction: Representation, estimation, and testing,"
Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
- Engle, Robert F & Granger, Clive W J, 1987. "Co-integration and Error Correction: Representation, Estimation, and Testing," Econometrica, Econometric Society, vol. 55(2), pages 251-276, March.
- Dolan Antenucci & Michael Cafarella & Margaret Levenstein & Christopher Ré & Matthew D. Shapiro, 2014. "Using Social Media to Measure Labor Market Flows," NBER Working Papers 20010, National Bureau of Economic Research, Inc.
- Lucia Kureková & Miroslav Beblavý & Anna Thum-Thysen, 2015. "Using online vacancies and web surveys to analyse the labour market: a methodological inquiry," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 4(1), pages 1-20, December.
- Hyndman, Rob J. & Khandakar, Yeasmin, 2008.
"Automatic Time Series Forecasting: The forecast Package for R,"
Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i03).
- Rob J. Hyndman & Yeasmin Khandakar, 2007. "Automatic time series forecasting: the forecast package for R," Monash Econometrics and Business Statistics Working Papers 6/07, Monash University, Department of Econometrics and Business Statistics.
- Concha Artola & Fernando Pinto & Pablo de Pedraza García, 2015. "Can internet searches forecast tourism inflows?," International Journal of Manpower, Emerald Group Publishing Limited, vol. 36(1), pages 103-116, April.
- 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.
- Concha Artola & Enrique Galán, 2012. "Tracking the future on the web: construction of leading indicators using internet searches," Occasional Papers 1203, Banco de España.
- Chris Stewart, 2011. "A note on spurious significance in regressions involving I(0) and I(1) variables," Empirical Economics, Springer, vol. 41(3), pages 565-571, December.
- Schmidt, Torsten & Vosen, Simeon, 2012. "Using Internet Data to Account for Special Events in Economic Forecasting," Ruhr Economic Papers 382, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
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- Emmanouil S. Rigas & Tatiana Pourliaka & Maria Papoutsoglou & Hariklia Proios, 2023. "Towards a topic modeling approach to semi-automatically detect self-reported stroke symptoms (FAST symptoms) and their correlation with aphasia types," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(2), pages 1321-1336, April.
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Keywords
Web scraping; Cointegration; Time series; Job vacancies;All these keywords.
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