A Sentiment-Enhanced Corruption Perception Index

By Yongquan Cao, Yingjie Fan, Sandile Hlatshwayo, Monica Petrescu, Zaijin Zhan

July 23, 2021

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Yongquan Cao, Yingjie Fan, Sandile Hlatshwayo, Monica Petrescu, and Zaijin Zhan. A Sentiment-Enhanced Corruption Perception Index, (USA: International Monetary Fund, 2021) accessed September 18, 2024

Disclaimer: 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.

Summary

Direct measurement of corruption is difficult due to its hidden nature, and measuring the perceptions of corruption via survey-based methods is often used as an alternative. This paper constructs a new non-survey based perceptions index for 111 countries by applying sentiment analysis to Financial Times articles over 2005–18. This sentiment-enhanced corruption perception index (SECPI) captures not only the frequncy of corruption related articles, but also the articles’ sentiment towards corruption. This index, while correlated with existing corruption perception indexes, offers some distinct advantages, including heightened sensitivity to current events (e.g., corruption investigations and elections), availability at a higher frequency, and lower costs to update. The SECPI is negatively correlated with business environment and institutional quality. Increases in the perceived incidence or scope of corruption influences economic agents’ behaviors, and thus economic dynamics. We found that when the SECPI is at least one standard deviation above the mean, the growth per capita falls by 0.65 percentage point on average, with more pronounced impacts for emerging market and low income countries.

Subject: Business environment, Corruption, Crime, Economic sectors, Emerging and frontier financial markets, Financial markets

Keywords: Articles' sentiment, Business environment, Corruption, Emerging and frontier financial markets, Global, Perception index, Sentiment analysis method, Statistic department, Summary statistics

Publication Details

Pages:

27
Volume:

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DOI:

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Issue:

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Series:

Working Paper No. 2021/192
Stock No:

WPIEA2021192
ISBN:

9781513588889
ISSN:

1018-5941

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