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

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  • François Robin

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.

Suggested Citation

  • François Robin, 2018. "Use of Google Trends Data in Banque de France Monthly Retail Trade Surveys," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 505-506, pages 35-63.
    • Handle: RePEc:nse:ecosta:ecostat_2018_505-506_3
    DOI: https://doi.org/10.24187/ecostat.2018.505d.1965
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    References listed on IDEAS

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    More about this item

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications

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