The Effect(s) of E-government on Corruption: Examining the Role of Development Level

E-government is one of the important innovations that has recently changed public administration. Although many governments have implemented e-government initiatives to reduce corruption in the public sector, the effectiveness of e-government in this regard is still a subject of debate. This paper examines the effectiveness of e-government in reducing corruption in the public sector for 168 countries from 2012 to 2022. Thus, this paper studies the relationship between the United Nations E-Government Development Index (EGDI) as the independent variable and corruption as the dependent variable, measured by the Corruption Perceptions Index developed by Transparency International and the Control of Corruption (COC) index alternately. To this end, three models were estimated: The baseline model examined the overall effect of the E-Government Development Index on corruption for the whole sample. The second one examined the impact of each sub-indicator of EGDI, namely, Online Service Index (OSI), Telecommunication Infrastructure Index (TII), and Human Capital Index (HCI), on corruption, also for the whole sample. Finally, the third model divided the data set into three subsets: developed, developing, and in-transition countries by adding a dummy variable to account for the development level, and compared the effect of EGDI on reducing corruption among the three groups of countries. The models were estimated using Ordinary Least Squares (OLS) fixed effects. The results of the baseline model showed that e-government can reduce corruption. As for the second model, results showed that OSI and HCI are significant. Finally, the third model showed that the impact of e-government on corruption is the highest in developing countries, followed by in-transition countries, and then developed countries. Therefore, this paper recommends a multi-faceted approach, encompassing e-government, institutional strengthening, transparency, and international cooperation to fight corruption effectively. Moreover, future research should address methodological limitations, such as employing panel dynamic analysis (e.g., GMM), and incorporate a wider range of indicators, including cultural, behavioral, and religious factors, to enhance the robustness of the findings.