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
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Persistent link: https://EconPapers.repec.org/RePEc:nse:ecosta:ecostat_2018_505-506_3

DOI: 10.24187/ecostat.2018.505d.1965

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