Group03 Proposal
Perceiving Evil: The Study of the Corruption Perception Index
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First launched in 1995, the Corruption Perceptions Index (CPI) has been widely credited with putting the issue of corruption on the forefront of the international policy agenda. Transparency International (TI), is an international non-governmental organization based in Berlin, Germany which acts to combat global corruption and prevent criminal activities arising from corruption. TI publishes the CPI, annually ranking countries "by their perceived levels of corruption, as determined by expert assessments and opinion surveys. The CPI generally defines corruption as "the misuse of public power for private benefit". The CPI currently ranks 176 countries on a scale from 100 (very clean) to 0 (highly corrupt). Denmark is the least corrupt country in the world, ranking consistently high among international financial transparency, while the most corrupt country in the world is North Korea, remaining on 8 out of 100 since 2012. In our project, we married the data set from Transparency International on their CPI records for specifically 2016 versus the World Bank data set through the years, which contains economical, agricultural, social, environmental data of the same countries. We will seek to find out if there is indeed any correlations between the perceived corruption level of a country, and its internal conditions.
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It has been a challenge to validate whether CPI is an accurate index to represent corruption. A study in 2002 found a “strong and significant correlation” between CPI and 2 proxies: black market activity and overabundance of regulation. But it is hard to find any clear indicators of black market activities and regulations. There were some claims by other studies as well:
There is also criticism in the usage of CPI’s methodology, some flaws pointed are:
The objective of our study is to find out if:
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The data came from two sources. The first one came from: https://www.kaggle.com/transparencyint/corruption-index The data set contains the following important columns:
The second data set from the World Bank came from: https://datacatalog.worldbank.org/dataset/world-development-indicators This data set is a collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates However, due to the huge amount of data, we only kept the data for countries which appeared in the CPI data set and only indices from 2006 to 2016. The filtered dataset for the World Bank data was 259,750 rows across 171 countries.
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The first factor to assess CPI is to understand the methodology of calculating the index. The CPI scores and ranks countries and territories around the world on the perceived level of corruption in the public sector. CPI is an aggregate index, which draws on relevant questions from several different data sources that capture business and expert views. In 2012, there is an updated methodology in calculating CPI. The following steps are followed to calculate the CPI:
We can also further analyse the CPI pre and post-2012 to see if there is an impact to the overall index score by country.
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R Studio, Tableau (only for preliminary EDA) and associated R libraries will be used:
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