IMF paper builds corruption indicator using big data
Corruption shocks negatively impact long-term real outcomes, authors say
New research published by the International Monetary Fund uses big data to assess the macroeconomic effects of corruption.
The team of researchers construct a ‘News Flow Indicator of Corruption’ (NIC) and its corruption-fighting counterpart, the anti-NIC, by running country-specific search algorithms on a newspaper database of more than 650 million articles, which record the number and intensity of news coverage that reference corruption.
The IMF working paper finds that on average NIC shocks
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