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2015 | 2 (48) | 9-22

Article title

Big data w statystyce publicznej – nadzieje, osiągnięcia, wyzwania i zagrożenia

Content

Title variants

EN
Big data in official statistics – hopes, achievements, challenges and risks

Languages of publication

PL

Abstracts

EN
The main purpose of the article is to describe the state of the art in using big data in official statistics. The article presents selected examples of how data from mobile operators, sensors, social media or scanners are used by national statistical offices. The authors also identify chances, challenges and risks related to the use of big data in the field of official statistics.

Contributors

References

  • Beręsewicz M., 2015, On the representativeness of Internet data sources for the real estate market in Poland, Austrian Journal of Statistics, 4(2).
  • Cavallo A., 2013, Online and official price indexes: Measuring Argentina’s inflation, Journal of Monetary Economics, 60(2), 152–165, doi:10.1016/j.jmoneco.2012.10.002.
  • Daas P.J.H., Puts M.J., Buelens B., Hurk P.A.M. van den, 2015, Big Data as a Source for Official Statistics, Journal of Official Statistics, 31(2), s. 249-262.
  • Eurostat, 2014, Feasibility Study of the Use of Mobile Positioning Data for Tourism Statistics, Consolidated Report Eurostat Contract No 30501.2012.001- 2012.452, 30.06.2014.
  • Griffioen R., de Haan J., Willenborg L., 2014, Collecting clothing data from the Internet, Statistics Netherlands, Den Haag.
  • Pfeffermann D., 2015, Official Statistics for the Next Decade – Methodological Issues and Challenges, referat wygłoszony na konferencji NTTS 2015, 10-12 marca 2015, Bruksela.
  • Porter A.T., Holan S.H., Wikle C.K., Cressie N., 2014, Spatial Fay–Herriot models for small area estimation with functional covariates, Spatial Statistics, 10, s. 27-42.
  • Puts M., Daas P., Teenekes M., 2015, High frequency road sensor data for official statisitics, referat wygłoszony na konferencji NTTS 2015, 10-12 marca 2015, Bruksela, dostęp online: http://www.cros-portal.eu/sites/default/files//Presentation%20S13AP4.pdf.
  • Swier N., 2015, Using Web Scraped Data to Construct Consumer Price Indices, referat wygłoszony na konferencji NTTS 2015, 10-12 marca 2015, Bruksela, http://www.cros-portal.eu/sites/default/files//Presentation%20S6AP3.pdf.
  • Szreder M., 2015, Big data wyzwaniem dla człowieka i statystyki, Wiadomości Statystyczne, Główny Urząd Statystyczny, sierpień, Warszawa.
  • Teenekes M., Marco P., 2015, High Frequency Road Sensor Data for Official Statisitics, referat wygłoszony na konferencji NTTS 2015, 10-12 marca 2015, Bruksela, http://www.cros-portal.eu/sites/default/files//Presentation%20S13AP5.pdf.
  • UNECE 2014, Big Data for Official Statistics, Technical Workshop Report, http://www1.unece.org/stat/platform/pages/viewpage.action?pageId=102664009.
  • Vicente M.R., López-Menéndez A.J., Pérez R., 2015, Technological Forecasting & Social Change Forecasting unemployment with internet search data: Does it help to improve predictions when job destruction is skyrocketing ?, Technological Forecasting & Social Change, 92, 132-139. doi:10.1016/j.techfore.2014.12.005.
  • Vosen S., Schmidt T., 2011, Forecasting Private Consumption: Survey-based Indicators vs. Google Trends, Journal of Forecasting, 578(1), s. 565-578.
  • Witkowski J., 2014, Statystyka oficjalna wobec wyzwań globalnych, Wiadomości Statystyczne, nr 4 (635), Główny Urząd Statystyczny, Polskie Towarzystwo Statystyczne.

Document Type

Publication order reference

Identifiers

YADDA identifier

bwmeta1.element.desklight-00f87358-0e20-46ac-a74e-27190216b4ec
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