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Research Article

Corruption and government revenue: Evidence of a non-linear relationship driven by crises

& ORCID Icon
Article: 2295733 | Received 21 Oct 2022, Accepted 10 Dec 2023, Published online: 22 Dec 2023

Figures & data

Table 1. List of variables and data sources.

Figure 1. Relationship between corruption and revenue in 1996 and 2020.

The fitted values (red line) are based on a bivariate linear regression. Countries with revenue-to-GDP ratios greater than one are excluded.
Source: Authors’ analysis.
Figure 1. Relationship between corruption and revenue in 1996 and 2020.

Figure 2. Revenues in high/low corruption countries over time.

High corruption countries are defined as those with a negative value of the “Control of Corruption” indicator from the Worldwide Governance Indicators (WGI) database (all others are considered low corruption countries).
Source: Authors’ analysis.
Figure 2. Revenues in high/low corruption countries over time.

Figure 3. Relationship between corruption and revenue in different country groups, 2020.

Income groups are defined according to World Bank classification. Democratic countries are defined as those with a Polity score above 5 (all others are considered non-democratic). Resource-poor countries are defined as those with total natural resources rents below 5 percent of GDP (all others are considered resource-rich). The fitted values (red lines) are based on bivariate linear regressions. Countries with revenue-to-GDP ratios greater than one are excluded. Data are for the year 2020.
Source: Authors’ analysis.
Figure 3. Relationship between corruption and revenue in different country groups, 2020.

Table 2. Regression results—dependent variable: revenue (% GDP).

Table 3. Results for high/low and middle-income countries—dependent variable: revenue (% GDP).

Table 4. Results for democratic/Non-democratic countries—dependent variable: revenue (% GDP).

Table 5. Results for resource-rich/Resource-poor countries—dependent variable: revenue (% GDP).