Global Demand and Supply Sentiment: Evidence From Earnings Calls
This paper quantifies global demand and supply conditions and compares two major global recessions: the 2009 Great Recession and the COVID‐19 pandemic. First, we compute demand and supply sentiment by applying Natural Language Processing techniques on earnings call transcripts. Second, we corroborat...
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| Veröffentlicht in: | Oxford bulletin of economics and statistics 2024-04, Vol.86 (2), p.314-334 |
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| creator | Ulrich Ruch, Franz Taskin, Temel |
| description | This paper quantifies global demand and supply conditions and compares two major global recessions: the 2009 Great Recession and the COVID‐19 pandemic. First, we compute demand and supply sentiment by applying Natural Language Processing techniques on earnings call transcripts. Second, we corroborate our sentiment measure by identifying demand and supply shocks using a structural Bayesian vector autoregression model. The results highlight sharp contrast in the size of supply and demand conditions over time and across sectors. While the Great Recession was characterized by weak demand, COVID‐19 caused sizable disruptions to both demand and supply, 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. |
| doi_str_mv | 10.1111/obes.12587 |
| format | Article |
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| ispartof | Oxford bulletin of economics and statistics, 2024-04, Vol.86 (2), p.314-334 |
| issn | 0305-9049 1468-0084 |
| language | eng |
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| source | Wiley Online Library Journals Frontfile Complete |
| subjects | 2008-2021 Bayesian analysis Branchenentwicklung Business services Coronavirus COVID-19 Department stores Earnings Gesamtwirtschaftliche Nachfrage Gesamtwirtschaftliches Angebot Great Recession Pandemics Recessions Retail stores Supply & demand USA Weltwirtschaftskrise |
| title | Global Demand and Supply Sentiment: Evidence From Earnings Calls |
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