BazEkon - The Main Library of the Cracow University of Economics

BazEkon home page

Main menu

Doligalski Tymoteusz (Warsaw School of Economics, Poland), Tomczyk Emilia (Warsaw School of Economics, Poland)
Nowcasting New Car Registrations with Google Search Data and Car Manufacturers' Website Traffic
Przedsiębiorczość i Zarządzanie, 2016, t. 17, z. 10, cz. 2, s. 147-154, tab., bibliogr. 8 poz.
Entrepreneurship and Management
Issue title
Zarządzanie w dobie ograniczonego zaufania
Wyszukiwarki internetowe, Witryny internetowe, Rynek samochodowy
Internet search engine, Internet websites, Car market
Google Inc.
The purpose of this paper is an attempt to nowcast (here: to predict in a short time horizon) new car registrations in Poland based on data of Google search queries and website traffic of car manufacturers. The study covers 47 monthly observations for six automotive makes. The strongest explanatory power is exhibited by the autoregressive component (number of registrations lagged one month), followed by the number of search queries. The website traffic of car manufacturers significantly influences the number of registrations in two out of six cases. (original abstract)
Full text
  1. Askitas N., Zimmermann K.F. (2009), Google Econometrics and Unemployment Forecasting, "Applied Economics Quarterly", 55 (2), 107-120.
  2. Bańbura M., Giannone D., Modugno M., Reichlin L. (2013), Now-Casting and the Real-Time Data Flow, Working Papers, European Central Bank, no. 1564.
  3. Carriere-Swallow Y., Labbe F. (2013), Nowcasting with Google Trends in an Emerging Market, "Journal of Forecasting", 32 (4), 289-298.
  4. Choi H., Varian H. (2011), Predicting the Present with Google Trends, "Economic Record", 88, 2-9. doi: 10.1111/j.1475-4932.2012.00809.
  5. Li N., Peng G., Chen H., Bao. J. (2013), A Prediction Study on E-commerce Orders Based on Site Search Data, 6th International Conference on Information Management, "Innovation Management and Industrial Engineering", 2, 314-318.
  6. Schmidt T., Vosen S. (2009), Forecasting Private Consumption: Survey-based Indicators vs. Google Trends, "Ruhr Economic Papers", 155.
  7. Sun B., Li B., Li G., Zhang K. (2013), Automobile Demand Forecasting: An Integrated Model of PLS Regression and ANFIS. Advances in Information Sciences & Service Sciences, 5(8), 429-436.
  8. Tomczyk E., Doligalski T. (2015), Predicting New Car Registrations: Nowcasting with Google Search and Macroeconomic Data [in:] Sł. Partycki (ed.), E-społeczeństwo w Europie Środkowej i Wschodniej. Teraźniejszość i perspektywy rozwoju, Wydawnictwo KUL, Lublin, 228-236.
Cited by
Share on Facebook Share on Twitter Share on Google+ Share on Pinterest Share on LinkedIn Wyślij znajomemu