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Web Reviews as a New Leading Indicator for Nowcasting Travel Expenditure in Balance of Payments Statistics

Author

Listed:
  • Oxana Babecka Kucharcukova
  • Jan Bruha
  • Petr Sterba

Abstract

This paper introduces a novel travel performance indicator derived from tourist reviews available online, utilizing text mining techniques. The time series generated is integrated as an explanatory variable into a small-scale empirical model of travel revenue and expenditure in the Czech Republic's balance of payments. The significance of online reviews for nowcasting is validated through various machine learning algorithms. The study also addresses empirical challenges, including trends in review data, the impact of the COVID-19 pandemic, and occasional methodological changes in official statistical series, and outlines strategies to overcome these obstacles. The findings suggest that the proposed model is a valuable addition to the Czech National Bank's nowcasting framework. To the best of our knowledge, this is the first study to combine text analysis with nowcasting of a BoP item, specifically travel services.

Suggested Citation

  • Oxana Babecka Kucharcukova & Jan Bruha & Petr Sterba, 2025. "Web Reviews as a New Leading Indicator for Nowcasting Travel Expenditure in Balance of Payments Statistics," Working Papers 2025/13, Czech National Bank, Research and Statistics Department.
    • Handle: RePEc:cnb:wpaper:2025/13
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    File URL: https://www.cnb.cz/export/sites/cnb/en/economic-research/.galleries/research_publications/cnb_wp/cnbwp_2025_13.pdf
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    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • F17 - International Economics - - Trade - - - Trade Forecasting and Simulation

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