Economics at your fingertips  

Use of Google Trends Data in Banque de France Monthly Retail Trade Surveys

Francois Robin ()

Economie et Statistique / Economics and Statistics, 2018, issue 505-506, 35-63

Abstract: [eng] Under its partnership with the Banque de France, the Federation of E Commerce and Distance Selling (Fédération du e commerce et de la vente à distance FEVAD) has provided monthly consumer online retail sales data since 2012. Pending the release of new data, the Banque de France carries out estimations, a task complicated by the growth of online retail. The autoregressive model (SARIMA(12)) used up to now can now be complemented by other statistical models that draw on exogenous data with a longer historical time series. This paper details the system of choices that results in the final forecast: data conversion, variable selection methods and forecasting approaches. In particular, Google queries, as measured by Google Trends, help enhance the predictive accuracy of the final model, obtained by combi¬ning single models.

JEL-codes: C11 C51 C53 E17 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

DOI: 10.24187/ecostat.2018.505d.1965

Access Statistics for this article

Economie et Statistique / Economics and Statistics is currently edited by Dominique Goux

More articles in Economie et Statistique / Economics and Statistics from Institut National de la Statistique et des Etudes Economiques (INSEE) Contact information at EDIRC.
Bibliographic data for series maintained by Veronique Egloff ().

Page updated 2023-04-01
Handle: RePEc:nse:ecosta:ecostat_2018_505-506_3