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The impact of corruption on government performance: evidence from South Korea

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Abstract

While some studies argue that a low level of corruption in the public sector is positively associated with a high level of firm performance, few studies investigate the impact of corruption on public organizations’ performance. Does corruption decrease performance in government agencies? Using the integrity assessment dataset and the government performance evaluation dataset, this study investigates 42 central public organizations in South Korea from 2014 to 2018. This study employs a probit model, a random-effects model, and time-lagged regression to capture the impacts of corruption. The findings show that a low level of corruption within public organizations is positively associated with a high-performance level under certain conditions. This outcome shows that fighting corruption might contribute to improved organizational performance in public organizations.

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Authors and Affiliations

  1. Korean National Police University, 100-50 Hwangsan-gil, Sinchang-myeon, Asan-si, Chungcheongnam-do, 31539, Republic of Korea

    Kyoung-sun Min

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  1. Kyoung-sun Min
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Correspondence to Kyoung-sun Min.

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Author Kyoung-sun Min was a senior deputy director at Anti-Corruption & Civil Rights Commission that generates the data sets.

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Appendix

Appendix

Tables 7 and 8 display the impacts of the integrity assessment in the current year on government performance evaluations in the present year from 2012 to 2018. The dependent variable is government performance evaluations in the present year. The results in Tables 7 and 8 do not correspond with the hypotheses: a high level of external integrity, internal integrity, and policy customer evaluations in the current year is not related to government performance evaluations in the present year. In Table 7, some control variables are statistically significant. Model II in Table 7 shows that the act of lowering assessment reliability in the present year has a positive effect on government performance evaluations in the present year with a 95 percent confidence interval. Models II, IV, and VI in Table 7 also show that organizations related to economic affairs have received better scores on government performance evaluations than other types of organizations with a 99 percent confidence interval. Models II and VI in Table 7 show that organizations with more employees achieve a high-performance level on government performance evaluations with a 95 percent confidence interval.

Table 7 Probit Model from 2012 to 2018 (Dependent Variable: Government Performance Evaluationt-0)
Full size table
Table 8 Probit Model with Random-Effects from 2012 to 2018 (Dependent Variable: Government Performance Evaluationt-0)
Full size table

Tables 9 and 10 show the impacts of the integrity assessment in the present year on government main project evaluations in the present year from 2012 to 2018. The dependent variable is government main project evaluations in the present year. The results in Tables 9 and 10 partly correspond with the hypotheses. While model II in Table 9 shows that a high level of external integrity in the current year is associated with a high-performance level on government primary project evaluations in the current year, the other models in Tables 9 and 10 show that a high level of integrity assessment in the present year is not related to the dependent variable. In Tables 9 and 10, some control variables are also statistically significant. Models II, IV, and VI in Tables 9 and 10 show that the act of lowering assessment reliability in the present year has a positive effect on government main project evaluations in the current year with a 95 percent or 99 percent confidence interval. Models II, IV, and VI in Table 9 also show that organizations related to economic affairs have received better scores on government performance evaluations than other types of organizations with a 99 percent confidence interval.

Table 9 Probit Model from 2012 to 2018 (Dependent Variable: Government Main Project Evaluationt-0)
Full size table
Table 10 Probit Model with Random-Effects from 2012 to 2018 (Dependent Variable: Government Main Project Evaluationt-0)
Full size table

Tables 11 and 12 show the integrity assessment impacts in the previous year on government main performance evaluations in the present year from 2012 to 2017. Since the dependent variable is government performance evaluations in the next year, the values of government main performance evaluations are arranged from 2013 to 2018. The results in Tables 11 and 12 partly correspond with the hypotheses. While model VI in Table 11 shows that a high level of policy customer evaluations in the previous year is associated with a high-performance level on government performance evaluations in the present year, the other models in Tables 11 and 12 show that a high level of integrity assessment is not related to the dependent variable. In Table 11, some control variables are also statistically significant. Models II, IV, and VI in Table 11 show that organizations related to economic affairs have received better scores on government performance evaluations than other types of organizations with a 99 percent confidence interval. Models II and VI in Table 11 also show that organizations with more employees achieve a high-performance level on government performance evaluations in the next year with a 95 or 99 percent confidence interval.

Table 11 Probit Model from 2012 to 2017 (Dependent Variable: Government Performance Evaluationt-0)
Full size table
Table 12 Probit Model with Random-Effects from 2012 to 2017 (Dependent Variable: Government Performance Evaluationt-0)
Full size table

Tables 13 and 14 show the integrity assessment impacts in the previous year on government main project evaluations in the present year from 2012 to 2017. Since the dependent variable is government main project evaluations in the next year, the values from government main project evaluations are arranged from 2013 to 2018. The results in Tables 13 and 14 partly correspond with the hypotheses. Models II and VI in Table 13 show that a high level of external integrity and policy customer evaluations in the previous year are associated with a high-performance level on government main project evaluations in the present year. However, the other models in Tables 13 and 14 show that a high level of the integrity assessment is not related to the dependent variable. In Table 13, some control variables are also statistically significant. Models II, IV, and VI in Table 13 show that organizations related to economic affairs have received better scores on government main project evaluations than other types of organizations with a 99 percent confidence interval. Models II and VI in Table 13 also show that organizations with more employees achieve a high-performance level of government main project evaluations with a 95 percent confidence interval.

Table 13 Probit Model from 2012 to 2017 (Dependent Variable: Government Main Project Evaluationt-0)
Full size table
Table 14 Probit Model with Random-Effects from 2012 to 2017 (Dependent Variable: Government Main Project Evaluationt-0)
Full size table

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Min, Ks. The impact of corruption on government performance: evidence from South Korea. Crime Law Soc Change 79, 319–345 (2023). https://doi.org/10.1007/s10611-022-10054-x

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