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Turning Words into Numbers: Measuring News Media Coverage of Shortages

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  • Lin Chen
  • Stephanie Houle

Abstract

We generate high-frequency and up-to-date indicators to monitor news media coverage of supply (raw, intermediate and final goods) and labour shortages in Canada. We use natural language processing to construct two news-based indicators and time-varying topic narratives to track Canadian media coverage of these shortages from 2000 to 2022. This makes our indicators an insightful alternative monitoring tool for policy. Notably, our indicators track well with monthly price indexes and measures from the Bank of Canada’s Business Outlook Survey, and they are highly correlated with commonly tracked indicators of supply constraint. Moreover, the news-based indicators reflect the attention of the public on pressing issues.

Suggested Citation

  • Lin Chen & Stephanie Houle, 2023. "Turning Words into Numbers: Measuring News Media Coverage of Shortages," Discussion Papers 2023-8, Bank of Canada.
    • Handle: RePEc:bca:bocadp:23-8
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    References listed on IDEAS

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    1. Larsen, Vegard H. & Thorsrud, Leif Anders & Zhulanova, Julia, 2021. "News-driven inflation expectations and information rigidities," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 507-520.
    2. Damjan Pfajfar & Emiliano Santoro, 2013. "News on Inflation and the Epidemiology of Inflation Expectations," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(6), pages 1045-1067, September.
    3. Daniel D. Lee & H. Sebastian Seung, 1999. "Learning the parts of objects by non-negative matrix factorization," Nature, Nature, vol. 401(6755), pages 788-791, October.
    4. Scott R. Baker & Nicholas Bloom & Steven J. Davis & Stephen J. Terry, 2020. "COVID-Induced Economic Uncertainty," NBER Working Papers 26983, National Bureau of Economic Research, Inc.
    5. Li, Xuerong & Shang, Wei & Wang, Shouyang, 2019. "Text-based crude oil price forecasting: A deep learning approach," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1548-1560.
    6. Lamla, Michael J. & Lein, Sarah M., 2014. "The role of media for consumers’ inflation expectation formation," Journal of Economic Behavior & Organization, Elsevier, vol. 106(C), pages 62-77.
    7. Vegard Høghaug Larsen & Leif Anders Thorsrud, 2022. "Asset returns, news topics, and media effects," Scandinavian Journal of Economics, Wiley Blackwell, vol. 124(3), pages 838-868, July.
    8. Eleni Kalamara & Arthur Turrell & Chris Redl & George Kapetanios & Sujit Kapadia, 2022. "Making text count: Economic forecasting using newspaper text," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 896-919, August.
    9. Veronica Guerrieri & Guido Lorenzoni & Ludwig Straub & Iván Werning, 2022. "Macroeconomic Implications of COVID-19: Can Negative Supply Shocks Cause Demand Shortages?," American Economic Review, American Economic Association, vol. 112(5), pages 1437-1474, May.
    10. Felix Kapfhammer & Vegard H. Larsen & Leif Anders Thorsrud, 2020. "Climate risk and commodity currencies," Working Paper 2020/18, Norges Bank.
    11. Shapiro, Adam Hale & Sudhof, Moritz & Wilson, Daniel J., 2022. "Measuring news sentiment," Journal of Econometrics, Elsevier, vol. 228(2), pages 221-243.
    12. Pitschner, Stefan, 2022. "Supply chain disruptions and labor shortages: COVID in perspective," Economics Letters, Elsevier, vol. 221(C).
    13. Angelico, Cristina & Marcucci, Juri & Miccoli, Marcello & Quarta, Filippo, 2022. "Can we measure inflation expectations using Twitter?," Journal of Econometrics, Elsevier, vol. 228(2), pages 259-277.
    14. Weitzman, Martin L, 1991. "Price Distortion and Shortage Deformation, or What Happened to the Soap?," American Economic Review, American Economic Association, vol. 81(3), pages 401-414, June.
    15. Qian, Yingyi, 1994. "A Theory of Shortage in Socialist Economies Based on the "Soft Budget Constraint."," American Economic Review, American Economic Association, vol. 84(1), pages 145-156, March.
    16. Leland Bybee & Bryan T. Kelly & Asaf Manela & Dacheng Xiu, 2021. "Business News and Business Cycles," NBER Working Papers 29344, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Marc-André Gosselin & Temel Taskin, 2023. "What Can Earnings Calls Tell Us About the Output Gap and Inflation in Canada?," Discussion Papers 2023-13, Bank of Canada.

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    More about this item

    Keywords

    Coronavirus disease (COVID-19); Econometric and statistical methods; Monetary policy and uncertainty; Recent economic and financial developments;
    All these keywords.

    JEL classification:

    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • 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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