Tutorial Package for: Text as Data in Economic Analysis
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https://dataverse.nl/citation?persistentId=doi:10.34894/KNDZ9T
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资源简介:
This tutorial package, comprising both data and code, accompanies the article and is designed primarily to allow readers to explore the various vocabulary-building methods discussed in the paper. The article discusses how to apply computational linguistics techniques to analyze largely unstructured corporate-generated text for economic analysis. As a core example, we illustrate how textual analysis of earnings conference call transcripts can provide insights into how markets and individual firms respond to economic shocks, such as a nuclear disaster or a geopolitical event: insights that often elude traditional non-text data sources. This approach enables extracting actionable intelligence, supporting both policy-making and strategic corporate decision-making. We also explore applications using other sources of corporate-generated text, including patent documents and job postings. By incorporating computational linguistics techniques into the analysis of economic shocks, new opportunities arise for real-time economic data, offering a more nuanced understanding of market and firm responses in times of economic volatility.
提供机构:
Federal Reserve Bank of St. Louis; Frankfurt School of Finance & Management; NL Analytics Inc.; London Business School; Boston University; Tilburg University
创建时间:
2025-01-01



