Uncertainty over Uncertainty: Investigating the Assumptions, Annotations, and Text Measurements of Economic Policy Uncertainty

Katherine Keith, Christoph Teichmann, Brendan O’Connor, Edgar Meij


Abstract
Methods and applications are inextricably linked in science, and in particular in the domain of text-as-data. In this paper, we examine one such text-as-data application, an established economic index that measures economic policy uncertainty from keyword occurrences in news. This index, which is shown to correlate with firm investment, employment, and excess market returns, has had substantive impact in both the private sector and academia. Yet, as we revisit and extend the original authors’ annotations and text measurements we find interesting text-as-data methodological research questions: (1) Are annotator disagreements a reflection of ambiguity in language? (2) Do alternative text measurements correlate with one another and with measures of external predictive validity? We find for this application (1) some annotator disagreements of economic policy uncertainty can be attributed to ambiguity in language, and (2) switching measurements from keyword-matching to supervised machine learning classifiers results in low correlation, a concerning implication for the validity of the index.
Anthology ID:
2020.nlpcss-1.13
Volume:
Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science
Month:
November
Year:
2020
Address:
Online
Venue:
NLP+CSS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
116–131
Language:
URL:
https://aclanthology.org/2020.nlpcss-1.13
DOI:
10.18653/v1/2020.nlpcss-1.13
Bibkey:
Cite (ACL):
Katherine Keith, Christoph Teichmann, Brendan O’Connor, and Edgar Meij. 2020. Uncertainty over Uncertainty: Investigating the Assumptions, Annotations, and Text Measurements of Economic Policy Uncertainty. In Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science, pages 116–131, Online. Association for Computational Linguistics.
Cite (Informal):
Uncertainty over Uncertainty: Investigating the Assumptions, Annotations, and Text Measurements of Economic Policy Uncertainty (Keith et al., NLP+CSS 2020)
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PDF:
https://aclanthology.org/2020.nlpcss-1.13.pdf
Video:
 https://slideslive.com/38940620