Economics at your fingertips  

Using Natural Language Processing to Measure COVID-19-Induced Economic Policy Uncertainty for Canada and the US*

Shafuillah Qureshi (), Ba Chu, Fanny S. Demers () and Michel Demers ()
Additional contact information
Shafuillah Qureshi: Department of Economics, Carleton University,
Fanny S. Demers: Department of Economics, Carleton University,
Michel Demers: Department of Economics, Carleton University,

No 22-01, Carleton Economic Papers from Carleton University, Department of Economics

Abstract: We develop an economic policy uncertainty (EPU) index for Canada and the US using natural language processing (NLP) methods. Our EPU-NLP index is based on an application of several algorithms, including a rapid automatic keyword extraction algorithm (RAKE), a combination of the RoBERTa and the Sentence-BERT algorithms, a PyLucene search engine, and the GrapeNLP local grammar engine. For comparison purposes, we also develop an index based on a strictly Boolean index. We find that the EPU-NLP index captures COVID-19 related uncertainty better than the Boolean index. Using a structural VAR approach, we found that an economic policy uncertainty shock with EPU-NLP results in larger declines in real GDP, employment, industrial production and the TSX index than with EPU-Boolean for Canada. Similar results were also found for the US: an EPU-NLP shock led to larger declines in industrial production, employment, real personal consumption expenditure, and S&P500 than EPU-Boolean. The SVAR model showed an abrupt contraction in economic variables both for Canada and the US in line with the COVID-19 impact. Moreover, an uncertainty shock (with the EPU-NLP) caused a much larger contraction in economic variables for the period including the COVID-19 pandemic, than for the period before COVID-19.

Pages: 23 pages
Date: 2022-01-18
New Economics Papers: this item is included in nep-big and nep-cmp
References: View references in EconPapers View complete reference list from CitEc

Published: Carleton Economics Papers

Downloads: (external link)
Our link check indicates that this URL is bad, the error code is: 404 Not Found

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Ordering information: This working paper can be ordered from

Access Statistics for this paper

More papers in Carleton Economic Papers from Carleton University, Department of Economics C870 Loeb Building, 1125 Colonel By Drive, Ottawa Ontario, K1S 5B6 Canada.
Bibliographic data for series maintained by Court Lindsay ().

Page updated 2024-04-19
Handle: RePEc:car:carecp:22-01