Corruption Perceptions Index: Methods, Rankings & Economic Impact

Country comparisons serve many purposes: economic, political, social, educational, and so on. Many countries — and likely all developed countries — conduct country comparisons focused on international trade and overall national economic status. The collection of international economic data has been increasingly influenced by sophisticated strategy and technique, largely because national fiscal markets are globally linked and multinational corporations engage at high rates with foreign supply chain vendors (Podobnik, et al., 2008). Measures such as the gross domestic product (GDP), the consumer price index (PCPI), general government gross and net debt, and purchasing power parity (PPP) are all used to understand the economic status, monetary exchange, and other fiscal dynamics in different countries ("WEO," 2014).

Discourse among economists is strongly skewed toward ratios, curves, slopes, and derivatives — each carefully constructed to reveal patterns and trends that would not otherwise be accessible or interpretable ("WEO," 2014). Indeed, it is because the data are quantitative that they are so comparable; moreover, statistical procedures are used to weight differences that might inadvertently skew outcomes, and to calculate the relationships between various measures, such as the CPI and GDP (Shao, et al., 2007). For example, to accomplish surveillance of other countries, the World Economic Outlook (WEO) produces a country database containing data on each country's currency, the type of national account used, historical and latest data on national accounts, whether chain-weighted methodology is used, and historical and latest data on the consumer price index (CPI). The Consumer Price Index (CPI) is a term used by economists to reflect changing monthly data on "prices that urban consumers pay for a representative basket of goods and services" ("Bureau of Labor Statistics," 2014).

Another organization that uses country-based data is the Organization for Economic Co-operation and Development (OECD). The OECD is known for examining patterns related to international trade and business. Its mission is to "promote policies that will improve the economic and social well-being of people around the world" ("OECD," 2014). The OECD measures national productivity and the flow of global investment and trade, and additionally sets international standards on matters as disparate as agriculture, taxation, pension systems, and chemical safety.

From its policy experience and the country data it collects, the OECD designs and recommends policies that can improve quality of life. At the core of OECD work is "a shared commitment to market economies backed by democratic institutions and focused on the wellbeing of all citizens" ("OECD," 2014). Tandem objectives of OECD work include substantially making "life harder for the terrorists, tax dodgers, crooked businessmen and others whose actions undermine a fair and open society" ("OECD," 2014). To these ends, the OECD holds a Convention on Combating Bribery of Foreign Public Officials in International Business Transactions. Each participating country agrees to treat foreign bribery as a crime for which individuals and enterprises are held responsible. The Convention is therefore instrumental in curbing the export of corruption globally, since roughly two-thirds of global exports and nearly 90 percent of foreign direct investment outflows are directly tied to the 41 signatory countries. To increase its influence and effectiveness, the OECD Working Group on Bribery conducts follow-up reviews of nine to ten countries annually.

While the OECD emphasizes fact-based policymaking and implementation, an organization known as Transparency International serves as an aggressive watchdog. Transparency International is one of many non-governmental organizations (NGOs) that monitor and publicize the performance of political groups and corporations. The particular type of performance that Transparency International focuses on is the level of corruption in countries and territories around the world. The instrument it uses to measure and communicate perceived levels of corruption is the Corruption Perceptions Index.

The Corruption Perceptions Index (CPI) 2013 measures the perceived levels of public sector corruption in 177 countries and territories ("Transparency International," 2014). It is important to take note of the word "perceived," as it holds considerable importance with respect to the data collection and analysis procedures used to generate the CPI. When the CPI was first developed, public opinion surveys were used to gather corruption data — this information was truly based on people's perception. Over years of application, the CPI drew on different sources, which made year-over-year comparisons difficult. However, the current CPI utilizes up to 12 institutional sources to build the case for each country, though most countries use far fewer data sources (see Table 2).

Currently, the institutions providing assessment or survey data include the African Development Bank, the Bertelsmann Foundation, the Economist Intelligence Unit, Freedom House, Global Insight, the International Institute for Management Development, the Political and Economic Risk Consultancy, Political Risk Services, the World Economic Forum, the World Bank, and the World Justice Project. These organizations, along with the specific survey or assessment each contributes, are listed below:

Survey and assessment rigor has increased since the CPI was first introduced. The strength of the current aggregated index is that a more reliable and robust measure of a phenomenon is achieved when measures are taken from a combination of sources rather than from each source independently. Current CPI data are derived from performance assessments by analyst groups, from surveys of business people, or from standing assessments and reports. It is generally understood that the CPI must measure the perception of corruption, since it would not be possible to measure corruption in absolute terms — that is, to count discrete incidences of corrupt behavior. The section below entitled "How Is Data Collected and Analyzed?" provides a more detailed discussion with examples of the data sources used to determine country rankings.

The purpose of the Corruption Perceptions Index is to make transparent the undesirable behaviors integral to the economic, political, and social functioning of countries around the world. These behaviors include abuse of power, bribery, and secret dealings by officials and non-officials in positions that affect the capacity of societies to conduct business and administer government ("Transparency International," 2014).

The rationale behind the Corruption Perceptions Index is that reform begins with transparency. The Index also makes salient the importance of cracking down on corruption, as that category encompasses much more than simply greasing the wheels of a society. Anti-corruption efforts include halting money laundering and a relentless pursuit of stolen assets in order to return them to their rightful owners ("Transparency International," 2014). Anti-corruption efforts also include fundamental political finance reform and initiatives to establish higher levels of transparency in public institutions ("Transparency International," 2014). Huguette Labelle, the chairperson of Transparency International, has underscored the need to move from exposure to termination:

"It is time to stop those who get away with acts of corruption. The legal loopholes and lack of political will in government facilitate both domestic and cross-border corruption, and call for our intensified efforts to combat the impunity of the corrupt" ("Transparency International," 2014).

The ranking of countries and territories on the Corruption Perceptions Index is dependent upon public sector corruption. The rankings indicate the level of public sector corruption on a scale of 0 to 100 (see Appendix I, Appendix II, and Appendix III). A ranking of zero (0) represents perceptions that the country or territory is highly corrupt. A ranking of one hundred (100) represents perceptions that the country or territory is, in the terminology of Transparency International, "very clean." The scores convey the positions of countries and territories in relation to each other. The indices are produced annually. The 2013 index shows rankings for 177 countries and territories. It is important to note that a perfect score is never given, and that 69 percent of countries and territories are ranked below 50 ("Transparency International," 2014). The obvious conclusion to be drawn from this is that global corruption is a serious problem, and that changing these normative societal states will be an enormous challenge.

For those disinclined to accept this conclusion, it is worthwhile to examine findings from economic research studies conducted in 2007 and 2008 that explicitly considered the consequences of corruption perception as determined by the CPI. Research conducted by Shao, et al. (2007) found a strong correlation between long-term economic growth at higher levels and better corruption perception scores on the CPI. Podobnik, et al. (2008) showed that for every unit a country's CPI score rose, there was a corresponding 1.7 percent increase in GDP growth. This relationship is apparent even through a visual inspection of the data, showing that the wealth of a country maps consistently to its corruption level, with the one notable exception of China.

Wilhelm (2002) found that there was a power-law dependence linking higher rates of foreign investment in a country to higher CPI scores. The simplest way to think about the power-law construct is to recall the Pareto distribution, commonly known as the 80-20 rule — a distribution applied to any convenient purpose by business people (Newman, 2006). Those familiar with The Black Swan by Nicholas Taleb will recognize the depiction of the long tail, and what it can mean for prediction models. By extension, on the topic of corruption, the X-axis would represent countries and the Y-axis would represent the perception of corruption incidence. This model only holds, however, as with all power-law dependencies, for limited numbers (Newman, 2006). That is to say that, in examining a map of countries considered to have high levels of corruption, only those countries with the worst CPI levels would appear at the intersection nearest zero in such a figure.

Wilhelm (2002) also conducted a study to validate the measures used to gauge and report levels of global corruption, and found a "very strong significant correlation of three measures of corruption" — a finding that indicates validity. The three measures were: (1) black market activity; (2) country scores on the Corruption Perceptions Index (CPI); and (3) the overabundance of regulation or unnecessary restriction of business activity. Moreover, "a highly significant correlation" was found between these three measures and gross domestic product per capita (RGDP/Cap). Notably, when testing the correlation with RGDP/Cap, the CPI accounted for more than 75 percent of the variance. The study of corruption in relation to business is not an empty exercise: corruption appears to actually deter country development and economic growth. As Wilhelm (2002) concludes, "Sustainable economic development appears very dependent on a constant, virtuous cycle that includes corruption fighting, and the maintenance of trust and innovation, all reinforcing each other."

The nature of corruption severely limits accurate assessment, as pointed out by Alex Cobham in a 2013 opinion piece in Foreign Policy, who states that, "Perceptions are not facts, and in this case they may also be an unhelpfully distorted reflection of the truth" (Cobham, 2013). Cobham simply expressed an opinion and offered no alternative facts — which, since this is what he criticized the CPI for routinely doing, does not add credibility to his comments. The level of his "analysis" can be sufficiently met with the counterargument: "Where there's smoke, there's fire."

It is true that absolute levels of corruption are hidden and not easily discernible. Corrupt illegal activities are concealed at all levels by the actors who engage in them ("Transparency International," 2014). Like the proverbial tip of the iceberg, when investigations, prosecutions, or scandals propel corrupt activities into the light, some measure of corruption is presumed — but it may be erroneous in either direction. Data based on prosecutions or investigations do not accurately represent the incidence or proclivity toward corruption in a society ("Transparency International," 2014). Rather, such data illustrate the effectiveness of the police, prosecutors, courts, and media in dredging up evidence of corruption, and they reflect the tacit agreements and social contracts that are normative in a culture ("Transparency International," 2014). There is general agreement that perceptions of corruption held by people in a position to assess the public sector provide "the most reliable method of comparing relative corruption levels across countries" ("Transparency International," 2014).

The discussion in the following paragraphs addresses the data collection and analysis process from top to bottom, first examining the 12 institutions that provide the 13 data sources, then considering the types of information obtained, and finally exploring the actual questions or topics covered at the survey or assessment level.

Scores to develop the Corruption Perceptions Index are taken from any of 13 sources shown in the table below (Saisana & Saltelli, 2012, p. 8). Countries that have been evaluated by three or more sources can be included in the index (Saisana & Saltelli, 2012, p. 8). For the 2012 Corruption Perceptions Index, the highest number of sources attributed to any one country was ten (i.e., Czech Republic, Hungary, India, Poland, South Korea) (Saisana & Saltelli, 2012, p. 8). Seven to eight sources were used to evaluate most countries in the 2012 CPI, with 19 countries evaluated by data from only two sources (Saisana & Saltelli, 2012, p. 8). With so many different data sources and unique scales being used to obtain data, a process of rescaling takes place in order to make comparisons possible. This process, which is similar to meta-analysis data preparation procedures, is detailed in Appendix III — Calculation Steps for the CPI Index Scores.

Table 2 shows the institutions currently participating in the CPI, along with the number of countries that utilize data from each institution.