IDEAS home Printed from https://ideas.repec.org/a/pal/ecolmr/v4y2010i12p59-95.html
   My bibliography  Save this article

Googling the present

Author

Listed:
  • Graeme Chamberlin

    (Office for National Statistics)

Abstract

SummaryGoogle Trends data provides weekly reports on the number of search queries made by people in a geographical area and by category. As over three quarters of those who access the Internet regularly are looking for information on goods and services ‐ this information may be a useful indicator of economic activity. For example, the volume of queries may relate to future patterns of spending. This article investigates this use of Google Trends data for various search categories, looking at its correlation with official data on retail sales, property transactions, car registrations and foreign trips.

Suggested Citation

  • Graeme Chamberlin, 2010. "Googling the present," Economic & Labour Market Review, Palgrave Macmillan;Office for National Statistics, vol. 4(12), pages 59-95, December.
    • Handle: RePEc:pal:ecolmr:v:4:y:2010:i:12:p:59-95
    as

    Download full text from publisher

    File URL: http://www.palgrave-journals.com/elmr/journal/v4/n12/pdf/elmr2010166a.pdf
    File Function: Link to full text PDF
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: http://www.palgrave-journals.com/elmr/journal/v4/n12/full/elmr2010166a.html
    File Function: Link to full text HTML
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Nymand-Andersen, Per & Pantelidis, Emmanouil, 2018. "Google econometrics: nowcasting euro area car sales and big data quality requirements," Statistics Paper Series 30, European Central Bank.
    2. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    3. Alessia Naccarato & Andrea Pierini & Stefano Falorsi, 2015. "Using Google Trend Data To Predict The Italian Unemployment Rate," Departmental Working Papers of Economics - University 'Roma Tre' 0203, Department of Economics - University Roma Tre.
    4. Torsten Schmidt & Simeon Vosen, 2012. "Using Internet Data to Account for Special Events in Economic Forecasting," Ruhr Economic Papers 0382, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
    5. Krzysztof DRACHAL, 2020. "Forecasting the Inflation Rate in Poland and U.S. Using Dynamic Model Averaging (DMA) and Google Queries," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 18-34, July.
    6. repec:zbw:rwirep:0382 is not listed on IDEAS
    7. van der Wielen, Wouter & Barrios, Salvador, 2021. "Economic sentiment during the COVID pandemic: Evidence from search behaviour in the EU," Journal of Economics and Business, Elsevier, vol. 115(C).
    8. 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.
    9. 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.
    10. Naccarato, Alessia & Falorsi, Stefano & Loriga, Silvia & Pierini, Andrea, 2018. "Combining official and Google Trends data to forecast the Italian youth unemployment rate," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 114-122.
    11. Javier Sebastian, 2016. "Blockchain in financial services: Regulatory landscape and future challenges," Working Papers 16/21, BBVA Bank, Economic Research Department.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:ecolmr:v:4:y:2010:i:12:p:59-95. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.palgrave-journals.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.