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Forecasting Russian Macroeconomic Indicators Based on Information from News and Search Queries

Author

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  • Filipp Ulyankin

    (Russian Presidential Academy of National Economy and Public Administration)

Abstract

Modern economic literature features quite a number of various indices of economic activity. Some of them are based on consumer and business surveys ('manual' indices), while others are based on unstructured data from the Internet ('automatic' indices). However, the question as to which of these approaches is the most effective remains open. In this paper, we compare several different indices of economic activity in terms of their explanatory and predictive power. We build automatic' indices using machine learning methods. Search queries, news articles and user comments under news posts from social media are used as source data. The analysis of the resulting indices of economic activity shows that the search and news indices Granger-cause 'manual' indices and also better explain and predict the set of macroeconomic variables selected for research. The good explanatory power of the current values of macroeconomic indicators by means of current indices of economic activity with a lag in the release of macroeconomic statistics makes them suitable for nowcasting.

Suggested Citation

  • Filipp Ulyankin, 2020. "Forecasting Russian Macroeconomic Indicators Based on Information from News and Search Queries," Russian Journal of Money and Finance, Bank of Russia, vol. 79(4), pages 75-97, December.
    • Handle: RePEc:bkr:journl:v:79:y:2020:i:4:p:75-97
    DOI: 10.31477/rjmf.202004.75
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    References listed on IDEAS

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    Cited by:

    1. Mikhaylov, Dmitry, 2023. "Macroeconomic Forecasting with the Use of News Data," Working Papers w20220250, Russian Presidential Academy of National Economy and Public Administration.

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    More about this item

    Keywords

    text analysis; sentiment analysis; economic uncertainty index; data analysis; machine learning;
    All these keywords.

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

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