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Public Perceptions of Canada’s Investment Climate: A Natural Language Processing-Based Approach
Author:
Flora Lutz
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Yuanchen Yang https://isni.org/isni/0000000404811396 International Monetary Fund

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Chengyu Huang https://isni.org/isni/0000000404811396 International Monetary Fund

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Series:
IMF Working Papers
Volume/Issue:
Volume 2024: Issue 165
Language:
English
Publication Date:
26 Jul 2024
DOI:
https://doi.org/10.5089/9798400284373.001
ISBN:
9798400284373
ISSN:
1018-5941
Pages:
40
Keywords:
Investment Climate; Canada; Machine Learning; Sentiment Analysis; muted productivity growth; investmest climate; investment flow; NLP-based indicator; Climate finance; Competition; Infrastructure; Productivity; Mining sector; Global
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IMF Working Papers describe research in progress by the author(s) and are published to elicit comments and to encourage debate. The views expressed in IMF Working Papers are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.
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Canada’s muted productivity growth during recent years has sparked concerns about the country’s investment climate. In this study, we develop a new natural language processing (NPL) based indicator, mining the richness of Twitter (now X) accounts to measure trends in the public perceptions of Canada’s investment climate. We find that while the Canadian investment climate appears to be generally favorable, there are signs of slippage in some categories in recent periods, such as with respect to governance and infrastructure. This result is confirmed by both survey-based and NLP-based indicators. We also find that our NLP-based indicators would suggest that perceptions of Canada’s investment climate are similar to perceptions of U.S. investment climate, except with respect to governance, where views of U.S. governance are notably more negative. Comparing our novel indicator relative to traditional survey-based indicators, we find that the NLP-based indicators are statistically significant in helping to predict investment flows, similar to survey-based measures. Meanwhile, the new NLP-based indicator offers insights into the nuances of data, allowing us to identify specific grievances. Finally, we construct a similar indicator for the U.S. and compare trends across countries.
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Cover IMF Working Papers
IMF Working Papers
ISSN:
1018-5941
Publisher:
International Monetary Fund