Abstract
Low trust in government and the widespread sense that public institutions are corrupt appears to be a global phenomenon, and a challenge to effective governance. We use the Global Corruption Barometer with responses from individuals in 117 countries to probe what drives citizen perceptions of corruption and propensity to pay bribes. Our analysis of the role of particular individual characteristics on perceptions of corruption (including age, gender, self-reported income level, education and employment status) suggests that there is at least somewhat of a common sense across individuals of how corrupt a particular service is in their country, but other—largely unobservable—factors account for most of any particular individual’s responses. A second analysis of the relationship between country averages of perceptions of corruption and country-level explanatory variables (including GDP per capita, democracy, inequality, the probability of bribe payment as well as a service performance measure for each service) shows a strong negative association between GDP per capita and perceptions of corruption and a strong positive association between bribe payments and perceptions of corruption. We find little evidence of association between service performance measures and country averages of corruption perceptions in a given sector. We repeat the same analyses on the individual and the country levels using bribe payment as our dependent variable. Our findings suggest that GDP per capita lowers perceptions of corruption through its influence on bribe payments. A plausible conclusion from that interpretation would be that the one reliable tool we appear to have to reduce perceptions of corruption is development and associated increases in GDP per capita itself.
We are grateful for assistance from Ben Crisman.
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Notes
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- 2.
Solé-Ollé and Sorribas-Navarro (2014).
- 3.
- 4.
Mungiu-Pippidi (2015) distinguishes between particularistic and personalistic societies where corruption is the norm, and those where norm-based “ethical universalism” is the default.
- 5.
Individual perceptions of corruption have been found to be consistently affected by factors including age, ethnicity, education, political affiliation (Olken 2009).
- 6.
Note that reported bribe-paying covers both a bribe payment by the survey respondent herself/himself or anyone living in their household. The question posed to respondents with regards to bribes is: “In the past 12 months, have you or anyone living in your household paid a bribe in any form to each of the following institutions/organizations?”
- 7.
Mostly 2010 for perceptions of corruption about political parties, education, the judiciary and the police and mostly 2007 for perceptions of corruption about medical services, permits, utilities and tax services.
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Mostly 2010 for most countries the country-level overall corruption perception variable is the average of perceptions about the education services, the judiciary and the police—weighted by the number of respondents. For some countries—depending on the data available in the most recent survey year—the overall corruption perception variable also includes medical-, permit-, utilities- and tax services. Perceptions about political parties are not included for any country.
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For a detailed description of these measures, see: https://www.freedomhouse.org/report/freedom-world-2015/methodology#.UuEq87Qo71I (Freedom House) and http://www.systemicpeace.org/polityproject.html (Polity 2 scores).
- 11.
Given that experts are specifically asked to consider bribes and corruption in their assessment of Freedom House’s individual rights measure, any causal argument regarding this measure and our corruption indicators would have to be made with considerable care.
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Between two consecutive survey years or between 2007 and 2009 (we have no 2008 observations in our data).
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- 14.
As categorized by the World Bank in FY 2016.
- 15.
Only regression tables with results for all countries (HICs and non-HICs combined) are included in the Appendix. Separate regression results tables for HICs and non-HICs are available from the authors on request.
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The average across all services is 2.9 for HICs and 3.5 for non-HICs. The differences for all sectors are statistically significant using a two-sample t test with unequal variance.
- 17.
For example, as countries get richer and more educated, citizens become more sensitive to corruption possibilities; as countries get even more rich and educated, perception of corruption decline, presumably as government services improve overall. We find a hint of this possibility in the regression results below, where the education effect is positive on perceptions in developing countries and negative in the high-income countries.
- 18.
In a bivariate regression with perceptions of corruption across sectors as the dependent variable and log GDP per capita as the right-hand side variable.
- 19.
In the case of political parties, the average perception of corruption about political parties is a noteworthy exception to this trend: GDP per capita is not statistically significantly associated with perceptions but—unlike in other services—the average ten-year GDP growth is. Perhaps growth is a good “outcome variable” for political parties. Using three-year growth, the result was not significant for low- and middle-income countries—results available from authors.
- 20.
Using top 10% income share as a measure of inequality produces similar results—available from the authors on request.
- 21.
We also examine the relationship between our country-level perceptions measure and other measures of corruption—the CPIA, expert responses to Bertelsmann Transformation Index’s (BTI) questions on impunity and corruption control, and expert responses to three questions regarding corruption in awarding jobs, business licenses and procurement contracts from the Quality of Government Institute’s (QoG) 2012 Expert Survey. We see no statistically significant correlation between the CPIA or the corruption-related BTI questions, but the three QoG assessments of corruption do show a significant association with our (GCB) country-level citizen perception aggregates. One potential explanation could be that the QoG questions we tested focus on specific instances of corruption (getting a job, getting a business license, procurement contract), which may be more aligned with citizens’ own experiences than indicators that assess government corruption overall (CPIA, BTI). Results available on request.
- 22.
At the same time, some bribe payments may not represent corruption but a misunderstanding on the part of citizens, for example if citizens report a payment to a head teacher that is voluntary for extra school supplies as mandatory and thus a bribe. This is what not all of the bribe-paying is included in the “actual corruption” circle.
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Dal Bo and Di Tella (2003).
- 24.
The authors could construct a simple dummy variable to capture whether the previous year there was a significant corruption scandal and whether this led to any action by the government.
- 25.
The difference in implementation of laws within a country will also lead to a difference in perceptions of corruption by citizens.
- 26.
This is in line with the “resistance to reforms” argument first highlighted by Fernandez and Rodrik (1991).
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Birdsall, N., Kenny, C., Diofasi, A. (2018). What Drives Citizen Perceptions of Government Corruption? National Income, Petty Bribe Payments and the Unknown. In: Basu, K., Cordella, T. (eds) Institutions, Governance and the Control of Corruption. International Economic Association Series. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-65684-7_10
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