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Using BREL to nowcast the Belgian business cycle: the role of survey data

Author

Listed:
  • Ch. Piette

    (National Bank of Belgium)

  • G. Langenus

    (National Bank of Belgium)

Abstract

The article assesses the usefulness of indicators taken from surveys carried out by the National Bank of Belgium for predicting Belgian GDP and other important quarterly macroeconomic aggregates. To this end, the authors use the recently created BREL now-casting platform that consists of targeted bridge models for different data availability scenarios. BREL is based upon an elastic-net regression approach that takes into account the ragged-edge nature of the data set. The results of their empirical analysis suggest that survey data clearly help to predict Belgian (but also European) macroeconomic developments, in particular for earlier estimates, when the relevant hard data, notably firms’ turnover and industrial production, are not yet available. They also show that forecast accuracy is higher when using disaggregated survey results, rather than just the headline consumer confidence and business sentiment indicators. In this connection, demand expectations in the manufacturing industry and the unemployment expectations in the consumer survey consistently feature among the best predictors for real GDP growth.

Suggested Citation

  • Ch. Piette & G. Langenus, 2014. "Using BREL to nowcast the Belgian business cycle: the role of survey data," Economic Review, National Bank of Belgium, issue i, pages 75-98, June.
    • Handle: RePEc:nbb:ecrart:y:2014:m:june:i:i:p:75-98
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Raïsa Basselier & David Antonio Liedo & Geert Langenus, 2018. "Nowcasting Real Economic Activity in the Euro Area: Assessing the Impact of Qualitative Surveys," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 14(1), pages 1-46, April.
    2. Ana Arencibia Pareja & Ana Gomez-Loscos & Mercedes de Luis López & Gabriel Perez-Quiros, 2020. "A Short Term Forecasting Model for the Spanish GDP and itsDemand Components," Revista Economía, Fondo Editorial - Pontificia Universidad Católica del Perú, vol. 43(85), pages 1-30.
    3. Sauvenier, Mathieu & Van Bellegem, Sébastien, 2023. "Goodness-of-fit test in high-dimensional linear sparse models," LIDAM Discussion Papers CORE 2023008, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. David de Antonio Liedo, 2014. "Nowcasting Belgium," Working Paper Research 256, National Bank of Belgium.
    5. Christophe Piette, 2016. "Predicting Belgium’s GDP using targeted bridge models," Working Paper Research 290, National Bank of Belgium.

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    More about this item

    Keywords

    Now-casting; bridge models; Belgium; business cycle;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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