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Global Demand and Supply Sentiment: Evidence from Earnings Calls

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  • Temel Taskin
  • Franz Ulrich Ruch

Abstract

This paper quantifies global demand, supply and uncertainty shocks and compares two major global recessions: the 2008–09 Great Recession and the COVID-19 pandemic. We use two alternate approaches to decompose economic shocks: text mining techniques on earnings calls transcripts and a structural Bayesian vector autoregression model. The results highlight sharp contrast in the size of supply and demand shocks over time and across sectors. While the Great Recession was characterized by demand shocks, COVID-19 caused sizable disruptions to both demand and supply. These shocks were broad-based with varying relative importance across major sectors. Furthermore, certain sub-sectors, such as professional and business services, internet retail, and grocery/department stores, fared better than others during the pandemic.

Suggested Citation

  • Temel Taskin & Franz Ulrich Ruch, 2023. "Global Demand and Supply Sentiment: Evidence from Earnings Calls," Staff Working Papers 23-37, Bank of Canada.
    • Handle: RePEc:bca:bocawp:23-37
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    More about this item

    Keywords

    Business fluctuations and cycles; International topics; Inflation and prices; Econometric and statistical methods; Coronavirus disease (COVID-19);
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • 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

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