A Sentiment-Enhanced Corruption Perception Index

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

No 2021/192, IMF Working Papers from International Monetary Fund

Abstract: 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.

Keywords: sentiment analysis method; perception index; statistic department; articles' sentiment; summary statistics; Corruption; Emerging and frontier financial markets; Business environment; Global (search for similar items in EconPapers)
Pages: 27
Date: 2021-07-23
New Economics Papers: this item is included in nep-big and nep-pol
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