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Words are the new numbers: A newsy coincident index of business cycles

Author

Listed:
  • Leif Anders Thorsrud
Abstract
In this paper I construct a daily business cycle index based on quarterly GDP and textual information contained in a daily business newspaper. The newspaper data is decomposed into time series representing newspaper topics using a Latent Dirichlet Allocation model. The business cycle index is estimated using the newspaper topics and a time-varying Dynamic Factor Model where dynamic sparsity is enforced upon the factor loadings using a latent threshold mechanism. I show that both contributions, the usage of newspaper data and the latent threshold mechanism, contribute towards the qualities of the derived index: It is more timely and accurate than commonly used alternative business cycle indicators and indexes, and, it provides the index user with broad based high frequent information about the type of news that drive or reflect economic fluctuations.

Suggested Citation

  • Leif Anders Thorsrud, 2016. "Words are the new numbers: A newsy coincident index of business cycles," Working Papers No 4/2016, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    • Handle: RePEc:bny:wpaper:0044
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Business cycles; Dynamic Factor Model; Latent Dirichlet Allocation (LDA);
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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