Forecasting unemployment with internet search data: Does it help to improve predictions when job destruction is skyrocketing?

Technological Forecasting and Social Change

Volumn 92, Issue , 2015, Pages 132-139

  Vicente, María Rosalía ^a   López Menéndez, Ana J ^a   Pérez, Rigoberto ^a  

^a UNIVERSITY OF OVIEDO   (Spain)

Author keywords

ARIMA; ARIMAX; Forecasting; Google indicators; Spain; Unemployment

Indexed keywords

EMPLOYMENT; INFORMATION RETRIEVAL; INTERNET; SEARCH ENGINES; WORLD WIDE WEB;

ARIMA; ARIMAX; ECONOMIC INDICATORS; EXPLANATORY VARIABLES; FORECASTING PERFORMANCE; INFORMATION SOURCES; SPAIN; UNEMPLOYMENT;

FORECASTING;

FORECASTING METHOD; INTERNET; NUMERICAL MODEL; SOCIOECONOMIC INDICATOR; UNEMPLOYMENT;

SPAIN;

EID: 84921065214     PISSN: 00401625     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.techfore.2014.12.005     Document Type: Article

References (49)

1. Akaike H. A new look at the statistical model identification. IEEE Trans. Autom. Control 1974, 19(6):716-723.
2. Anvik C., Gjelstad K. Just Google it. Forecasting Norwegian unemployment figures with web queries. Working Paper N. 11 2010, Center for Research in Economics and Management.
3. Artola C., Galán E. Tracking the future on the web: construction of leading indicators using internet searches. Working Paper N. 1203 2012, Bank of Spain.
4. Askitas N., Zimmermann K.F. Google econometrics and unemployment forecasting. Appl. Econ. Q. 2009, 55(2):107-120.
5. Bing Pan D.C.W., Song H. Forecasting hotel room demand using search engine data. J. Hosp. Tour. Technol. 2012, 3(3):196-210.
6. Box G.E.P., Jenkins G.M. Time Series Analysis, Forecasting and Control 1970, Holden Day, San Francisco.
7. Bureau of Labour Statistics Labour Force Statistics from the Current Population Survey Available from:. http://data.bls.gov/timeseries/LNS14000000.
8. Carrière-Swallow Y., Labbé F. Nowcasting with Google Trends in an emerging market. J. Forecast. 2013, 32(4):289-298.
9. Chamberlin G. Googling the present. Economic and Labour Market Review 2010, 4 (12). UK Office for National Statistics.
10. Choi H., Varian H. Predicting the present with Google Trends. Technical Report, Google 2009, (Available from: http://google.com/googleblogs/pdfs/google_predicting_the_present.pdf).
11. Choi H., Varian H. Predicting initial claims for unemployment insurance using Google Trends. Technical Report, Google 2009, (Available from: http://research.google.com/archive/papers/initialclaimsUS.pdf).
12. D'Amuri F. Predicting unemployment in short samples with internet job search query data. MPRA Paper No. 18403 2009.
13. D'Amuri F., Marcucci J. Google it! Forecasting the US unemployment rate with a Google Job Search Index. MPRA Paper No. 18732 2009.
14. Da Z., Engelberg J., Gao P. In search of attention. J. Financ. 2011, 66(5):1461-1499.
15. Della Penna N., Huang H. Constructing consumer sentiment index for U.S. using Google searches. Working Papers 2009-26 2009, University of Alberta, Department of Economics.
16. Dickey D.A., Fuller W.A. Distribution of the estimators for autoregressive time series with a unit root. J. Am. Stat. Assoc. 1979, 74(366):427-431.
17. Dickey D.A., Hasza H.P., Fuller W.A. Testing for unit roots in seasonal times series. J. Am. Stat. Assoc. 1984, 79:355-367.
18. Ettredge M., Gerdes J., Karuga G. Using Web-based search data to predict macroeconomic statistics. Commun. ACM 2005, 48(11):87-92.
19. Eurostat Information Society Statistics at the Regional Level Available from:. http://epp.eurostat.ec.europa.eu/statistics_explained/index.php/Information_society_statistics_at_regional_level.
20. Eurostat Euro area unemployment rate at 12.0%, news release Available from:. http://epp.eurostat.ec.europa.eu/cache/ITY_PUBLIC/3-31012014-AP/EN/3-31012014-AP-EN.PDF.
21. Eurostat Information Society Statistics Available from:. http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=isoc_ci_ac_i&lang=en.
22. Fondeur Y., Karamé F. Can Google data help predict French youth unemployment?. Econ. Model. 2013, 30:117-125.
23. Gómez-Uranga M., Miguel J.C., Zabal-Iturriagagoitia J.M. Epigenetic economic dynamics: the evolution of big internet business ecosystems, evidence for patents. Technovation 2014, 34:177-189.
24. Google Google Trends Available from:. http://www.google.com/insights/search.
25. Guzman G. Internet search behavior as an economic forecasting tool: the case of inflation expectations. J. Econ. Soc. Meas. 2011, 36(3):119-167.
26. Joseph K., Babajide-Wintoki M., Zhang Z. Forecasting abnormal stock returns and trading volume using investor sentiment: evidence from online search. Int. J. Forecast. 2011, 27(4):1116-1127.
27. Jun S.-P., Park D.-H., Yeom J. The possibility of using search traffic information to explore consumer product attitudes and forecast consumer preference. Technol. Forecast. Soc. Chang. 2014, 86:237-253.
28. Kholodilin K., Podstawski M., Siliverstovs B. Do Google searches help in nowcasting private consumption? A real-time evidence for the US. Working Paper No. 256, KOF 2010.
29. Kwiatkowski D., Phillips P.C.B., Schmidt P., Shin Y. Testing the null hypothesis of stationarity against the alternative of a unit root. J. Econ. 1992, 54:159-178.
30. Lindberg F. Nowcasting Swedish retail sales with Google search query data 2011, (Master's Thesis), Stockholm University, (Available from: http://www.ne.su.se/education/master/econ_master/year2_thesis/theses/02_lindberg_f.pdf).
31. McLaren N., Shanbhogue R. Using internet search data as economic indicators 2011, Bank of England Quarterly Bulletin, (Available from: June http://www.bankofengland.co.uk/publications/quarterlybulletin/qb110206.pdf).
32. Ministry of Employment and Social Security Movimiento laboral registrado Available from:. http://www.empleo.gob.es/series/.
33. Ministry of Industry, Energy and Tourism Encuesta de coyuntura industrial Available from:. http://www.minetur.gob.es/es-ES/IndicadoresyEstadisticas/Industria/EncuestaCoyuntura/Paginas/encuesta-coyuntura.aspx.
34. Montgomery A.L., Zarnowitz V., Tsay R.S., Tiao G.C. Forecasting the U.S. unemployment rate. J. Am. Stat. Assoc. 1998, 93:478-493.
35. National Institute of Statistics Economically active population survey Available from:. http://www.ine.es/en/inebaseDYN/epa30308/epa_inicio_en.htm.
36. National Institute of Statistics Survey on the equipment and use of information and communication technologies (ICT-H) in households Available from:. http://www.ine.es/jaxi/menu.do?type=pcaxis&path=%2Ft25%2Fp450&file=inebase&L=1.
37. Preis T., Reith D., Stanley H.E. Complex dynamics of our economic life on different scales: insights from search engine query data. Philos. Trans. R. Soc. Lond. 2010, 5707-5719.
38. Schwarz G.E. Estimating the dimension of a model. Ann. Stat. 1978, 6(2):461-464.
39. Siganos A. Google attention and target price run ups. Int. Rev. Financ. Anal. 2013, 29:219-226.
40. Smith G.P. Google Internet search activity and volatility prediction in the market for foreign currency. Financ. Res. Lett. 2012, 9:103-110.
41. Suhoy T. Query indices and a 2008 downturn: Israeli data. Technical Report 2009, Bank of Israel, (Available from: http://www.bankisrael.gov.il/deptdata/mehkar/papers/dp0906e.pdf).
42. Theil H. Applied Economic Forecasting 1966, North Holland Publishing, Amsterdam.
43. Varian H.R. Big data: new tricks for econometrics. Working Paper 2013, (Available at: http://people.ischool.berkeley.edu/~hal/Papers/2013/ml.pdf).
44. Vlastakis N., Markellos R.N. Information demand and stock market volatility. J. Bank. Financ. 2012, 36(6):1808-1821.
45. Vosen S., Schmidt T. Forecasting private consumption: survey-based indicators vs. Google Trends. J. Forecast. 2011, 30(6):565-578.
46. Vosen S., Schmidt T. A monthly consumption indicator for Germany based on Internet search query data. Appl. Econ. Lett. 2012, 19(7):683-687.
47. Vosen S., Schmidt T. Using Internet Data to Account for Special Events in Economic Forecasting 2012, Social Science Research Network, (Available from: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2200402).
48. Webb G.K. Internet search statistics as a source of business intelligence: searches on foreclosure as an estimate of actual home foreclosures. Issues Inf. Syst. 2009, 10(2):82-87.
49. Wu L., Brynjolfsson E. The future of prediction: how Google searches foreshadow housing prices and sales. Technical Report 2010, MIT, (Available from: http://www.nber.org/confer/2009/PRf09/Wu_Brynjolfsson.pdf).