ETLAnow: A Model for Forecasting with Big Data – Forecasting Unemployment with Google Searches in Europe
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- Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2008.
"Nowcasting: The real-time informational content of macroeconomic data,"
Journal of Monetary Economics, Elsevier, vol. 55(4), pages 665-676, May.
- Domenico Giannone & Lucrezia Reichlin & David H. Small, 2005. "Nowcasting GDP and inflation: the real-time informational content of macroeconomic data releases," Finance and Economics Discussion Series 2005-42, Board of Governors of the Federal Reserve System (U.S.).
- Domenico Giannone & Lucrezia Reichlin & David H Small, 2007. "Nowcasting GDP and Inflation: The Real-Time Informational Content of Macroeconomic Data Releases," Money Macro and Finance (MMF) Research Group Conference 2006 164, Money Macro and Finance Research Group.
- Reichlin, Lucrezia & Giannone, Domenico & Small, David, 2005. "Nowcasting GDP and Inflation: The Real Time Informational Content of Macroeconomic Data Releases," CEPR Discussion Papers 5178, C.E.P.R. Discussion Papers.
- Liran Einav & Jonathan Levin, 2014.
"The Data Revolution and Economic Analysis,"
Innovation Policy and the Economy, University of Chicago Press, vol. 14(1), pages 1-24.
- Liran Einav & Jonathan Levin, 2013. "The Data Revolution and Economic Analysis," NBER Chapters, in: Innovation Policy and the Economy, Volume 14, pages 1-24, National Bureau of Economic Research, Inc.
- Liran Einav & Jonathan D. Levin, 2013. "The Data Revolution and Economic Analysis," NBER Working Papers 19035, National Bureau of Economic Research, Inc.
- Liran Einav & Johnathan Levin, 2013. "The Data Revolution and Economic Analysis," Discussion Papers 12-017, Stanford Institute for Economic Policy Research.
- 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.
- Scott R. Baker & Andrey Fradkin, 2017. "The Impact of Unemployment Insurance on Job Search: Evidence from Google Search Data," The Review of Economics and Statistics, MIT Press, vol. 99(5), pages 756-768, December.
- D’Amuri, Francesco & Marcucci, Juri, 2017.
"The predictive power of Google searches in forecasting US unemployment,"
International Journal of Forecasting, Elsevier, vol. 33(4), pages 801-816.
- Francesco D'Amuri & Juri Marcucci, 2012. "The predictive power of Google searches in forecasting unemployment," Temi di discussione (Economic working papers) 891, Bank of Italy, Economic Research and International Relations Area.
- Tuhkuri, Joonas, 2014. "Big Data: Google Searches Predict Unemployment in Finland," ETLA Reports 31, The Research Institute of the Finnish Economy.
- Avi Goldfarb & Shane M. Greenstein & Catherine E. Tucker, 2015. "Economic Analysis of the Digital Economy," NBER Books, National Bureau of Economic Research, Inc, number gree13-1, June.
- 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.
- Croushore, Dean, 2006. "Forecasting with Real-Time Macroeconomic Data," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 17, pages 961-982, Elsevier.
- Kory Kroft & Devin G. Pope, 2014.
"Does Online Search Crowd Out Traditional Search and Improve Matching Efficiency? Evidence from Craigslist,"
Journal of Labor Economics, University of Chicago Press, vol. 32(2), pages 259-303.
- Kroft, Kory & Pope, Devin G., 2012. "Does Online Search Crowd Out Traditional Search and Improve Matching Efficiency? Evidence from Craigslist," CLSSRN working papers clsrn_admin-2012-35, Vancouver School of Economics, revised 30 Nov 2012.
- Domenico Giannone & Lucrezia Reichlin & David H. Small, 2005.
"Nowcasting GDP and inflation: the real-time informational content of macroeconomic data releases,"
Finance and Economics Discussion Series
2005-42, Board of Governors of the Federal Reserve System (U.S.).
- Giannone, Domenico & Reichlin, Lucrezia & Small, David H., 2006. "Nowcasting GDP and inflation: the real-time informational content of macroeconomic data releases," Working Paper Series 633, European Central Bank.
- Domenico Giannone & Lucrezia Reichlin & David H Small, 2007. "Nowcasting GDP and Inflation: The Real-Time Informational Content of Macroeconomic Data Releases," Money Macro and Finance (MMF) Research Group Conference 2006 164, Money Macro and Finance Research Group.
- Reichlin, Lucrezia & Giannone, Domenico & Small, David, 2005. "Nowcasting GDP and Inflation: The Real Time Informational Content of Macroeconomic Data Releases," CEPR Discussion Papers 5178, C.E.P.R. Discussion Papers.
- 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.
- 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.
- Tuhkuri, Joonas, 2016. "Forecasting Unemployment with Google Searches," ETLA Working Papers 35, The Research Institute of the Finnish Economy.
- Peter Kuhn & Mikal Skuterud, 2004.
"Internet Job Search and Unemployment Durations,"
American Economic Review, American Economic Association, vol. 94(1), pages 218-232, March.
- Kuhn, Peter J. & Skuterud, Mikal, 2002. "Internet Job Search and Unemployment Durations," IZA Discussion Papers 613, Institute of Labor Economics (IZA).
- Kuhn, Peter & Skuterud, Mikal Skuterud, 2002. "Internet Job Search and Unemployment Durations," University of California at Santa Barbara, Economics Working Paper Series qt8583s24x, Department of Economics, UC Santa Barbara.
- S. Boragan Aruoba & Francis X. Diebold, 2010.
"Real-Time Macroeconomic Monitoring: Real Activity, Inflation, and Interactions,"
American Economic Review, American Economic Association, vol. 100(2), pages 20-24, May.
- S. Boragan Aruoba & Francis X. Diebold, 2010. "Real-Time Macroeconomic Monitoring: Real Activity, Inflation, and Interactions," PIER Working Paper Archive 10-002, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- S. Boragan Aruoba & Francis X. Diebold, 2010. "Real-time macroeconomic monitoring: real activity, inflation, and interactions," Working Papers 10-5, Federal Reserve Bank of Philadelphia.
- S. Boragan Aruoba & Francis X. Diebold, 2010. "Real-Time Macroeconomic Monitoring: Real Activity, Inflation, and Interactions," NBER Working Papers 15657, National Bureau of Economic Research, Inc.
- Helmut Lütkepohl & Fang Xu, 2012.
"The role of the log transformation in forecasting economic variables,"
Empirical Economics, Springer, vol. 42(3), pages 619-638, June.
- Helmut Lütkepohl & Fang Xu, 2009. "The Role of the Log Transformation in Forecasting Economic Variables," CESifo Working Paper Series 2591, CESifo.
- 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.
- Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
- Betsey Stevenson, 2009.
"The Internet and Job Search,"
NBER Chapters, in: Studies of Labor Market Intermediation, pages 67-86,
National Bureau of Economic Research, Inc.
- Betsey Stevenson, 2008. "The Internet and Job Search," NBER Working Papers 13886, National Bureau of Economic Research, Inc.
- Goldfarb, Avi & Greenstein, Shane M. & Tucker, Catherine E. (ed.), 2015. "Economic Analysis of the Digital Economy," National Bureau of Economic Research Books, University of Chicago Press, number 9780226206981, October.
- Lynn Wu & Erik Brynjolfsson, 2015. "The Future of Prediction: How Google Searches Foreshadow Housing Prices and Sales," NBER Chapters, in: Economic Analysis of the Digital Economy, pages 89-118, National Bureau of Economic Research, Inc.
- 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.
- Cochrane, John H., 1991. "A critique of the application of unit root tests," Journal of Economic Dynamics and Control, Elsevier, vol. 15(2), pages 275-284, April.
- Domenico Giannone & Lucrezia Reichlin & David Small, 2008. "Nowcasting: the real time informational content of macroeconomic data releases," ULB Institutional Repository 2013/6409, ULB -- Universite Libre de Bruxelles.
- Jeremy Ginsberg & Matthew H. Mohebbi & Rajan S. Patel & Lynnette Brammer & Mark S. Smolinski & Larry Brilliant, 2009. "Detecting influenza epidemics using search engine query data," Nature, Nature, vol. 457(7232), pages 1012-1014, February.
- 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.
- Arellano, M, 1987. "Computing Robust Standard Errors for Within-Groups Estimators," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 49(4), pages 431-434, November.
- Manuel Arellano & Stephen Bond, 1991.
"Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations,"
The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
- Tom Doan, "undated". "RATS program to replicate Arellano-Bond 1991 dynamic panel," Statistical Software Components RTZ00169, Boston College Department of Economics.
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Cited by:
- Anttonen, Jetro, 2018. "Nowcasting the Unemployment Rate in the EU with Seasonal BVAR and Google Search Data," ETLA Working Papers 62, The Research Institute of the Finnish Economy.
- Cristea, R. G., 2020. "Can Alternative Data Improve the Accuracy of Dynamic Factor Model Nowcasts?," Cambridge Working Papers in Economics 20108, Faculty of Economics, University of Cambridge.
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More about this item
Keywords
Big Data; Google; Internet; Nowcasting; Forecasting; Unemployment; Europe;All these keywords.
JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
- C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
- E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
NEP fields
This paper has been announced in the following NEP Reports:- NEP-CMP-2016-06-09 (Computational Economics)
- NEP-EUR-2016-06-09 (Microeconomic European Issues)
- NEP-MAC-2016-06-09 (Macroeconomics)
- NEP-ORE-2016-06-09 (Operations Research)
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