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Now- and Backcasting Initial Claims with High-Dimensional Daily Internet Search-Volume Data

Author

Listed:
  • Daniel Borup

    (Aarhus University, CREATES and the Danish Finance Institute (DFI))

  • David E. Rapach

    (Washington University in St. Louis and Saint Louis University)

  • Erik Christian Montes Schütte

    (Aarhus University, CREATES and the Danish Finance Institute (DFI))

Abstract

We generate a sequence of now- and backcasts of weekly unemployment insurance initial claims (UI) based on a rich trove of daily Google Trends (GT) search-volume data for terms related to unemployment. To harness the information in a high-dimensional set of daily GT terms, we estimate predictive models using machine-learning techniques in a mixed-frequency framework. In a simulated out-of-sample exercise, now- and backcasts of weekly UI that incorporate the information in the daily GT terms substantially outperform models that ignore the information. The relevance of GT terms for predicting UI is strongly linked to the COVID-19 crisis.

Suggested Citation

  • Daniel Borup & David E. Rapach & Erik Christian Montes Schütte, 2021. "Now- and Backcasting Initial Claims with High-Dimensional Daily Internet Search-Volume Data," CREATES Research Papers 2021-02, Department of Economics and Business Economics, Aarhus University.
    • Handle: RePEc:aah:create:2021-02
    as

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    File URL: https://repec.econ.au.dk/repec/creates/rp/21/rp21_02.pdf
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Unemployment insurance; Internet search; Mixed-frequency data; Penalized regression; Neural network; Variable importance;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • J65 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment Insurance; Severance Pay; Plant Closings

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