E-government as an anti-corruption tool: panel data analysis across countries

Abstract

Over the past two decades, many governments around the world have adopted e-government as an anti-corruption tool. However, there is a lack of empirical evidence on the impacts of e-government on corruption. Thus, this article aims to empirically examine whether e-government reduces corruption across countries. For this purpose, longitudinal data from 2003 to 2016 were collected from 214 countries and then panel data analysis based on a fixed-effect model was conducted. Analysis results reveal that e-government as a whole significantly reduces corruption, while the effects of open government as one type of e-government are unclear. However, the rule of law moderates the relationship between open government and corruption. That is, in countries with more effective legal systems, open government is more likely to reduce corruption than in countries with less effective legal systems.

Points for practitioners

E-government as a whole can effectively reduce corruption.

Open government, such as open data portals and online discussion forums, does not have a direct impact on the reduction of corruption.

Open government can have a conditional impact on corruption, relying on the effectiveness of legal systems.

Keywords

anti-corruption corruption e-government open government

Introduction

For the past two decades, many governments across the globe have adopted diverse e-government initiatives that utilize information and communication technologies (ICTs) to improve their internal operations and service delivery systems, and to effectively communicate with non-state stakeholders, including the general public, non-profit organizations, and for-profit corporations. For example, the Seoul Metropolitan Government of South Korea launched an online application system called Online Procedures ENhancement (OPEN) for civil applications. Citizens can submit their various applications for permits and procurements, and track the review and approval status in real time by using the online system (Bertot et al., 2010; Cho and Choi, 2004). During the Obama administration in the US, President Obama ordered an Open Government Directive in 2009. The directive aimed to make government more transparent, participative, and collaborative by using ICTs that allow non-state stakeholders to more actively participate in policy decision-making and implementation processes (Wirtz and Birkmeyer, 2015).

This article focuses on e-government as an anti-corruption strategy. In the corruption literature, scholars and practitioners have paid little attention to this research topic. Specifically, this article intends to empirically examine whether e-government initiatives curb corruption. Over the past decade, several scholars have sought to answer this research question (Cho and Choi, 2004; Pathak et al., 2008), but a causal relationship between e-government and corruption is still unclear due to the methodological limitations of prior studies based on qualitative case-study methods and cross-sectional quantitative data and correlation research. Thus, in this article, longitudinal data from 2003 to 2016 were collected from 214 countries and then quantitative data analysis for causal inference based on a fixed-effect model was conducted, controlling for various political, societal, economic, and technological factors.

This research is important for several theoretical and practical reasons. First, this research can contribute to the literature by empirically examining the effects of e-government on curbing corruption and ultimately integrating the corruption literature and the e-government literature, which have previously been quite disconnected. Also, empirical findings from this research can be used by practitioners to create evidence-based anti-corruption strategies.

Literature review

Corruption

Corruption frequently refers to acts “in which public officials, bureaucrats, legislators, and politicians use powers delegated to them by the public to further their own … interests at the expense of the common good” (Jain, 2001: 73). The corruption literature has primarily focused on three key topics: determinants of corruption; consequences of corruption; and anti-corruption strategies.

Many prior studies have explored various determinants of corruption in both qualitative and quantitative manners:

economic factors: gross domestic product (GDP) per capita (Fan et al., 2009) and trade openness (Treisman, 2000);

judicial factors: punishment for corruption (Jain, 2001; Mauro, 1998; Tanzi, 1998);

political factors: level of democracy (Chowdhury, 2004) and political stability (Serra, 2006);

public administration factors: bureaucratic red tape (Tanzi, 1998) and public sector pay and recruitment (Van Rijckeghem and Weder, 2001);

societal and cultural factors: education (Kolstad and Wiig, 2009) and press freedom (Brunetti and Weder, 2003); and

technological factors: Internet and mobile subscriptions (Lio et al., 2011; Relly, 2012).

In particular, levels of corruption were lower in countries that were economically developed, had fewer natural resources, were more open to international trade, and had more effective judicial systems. However, levels of corruption were higher in countries with lower levels of democracy and political stability, and with a presidential political system. Levels of public sector pay were negatively associated with corruption.

Many scholars and practitioners have also investigated the consequences of corruption. Corruption tends to lower private investment and ultimately decrease economic growth (Aidt et al., 2008; Seligson, 2002). Importantly, corruption is likely to distort government procurement processes, increasing inefficiency and unfairness in government contracting (Rose-Ackerman, 1996). Furthermore, corruption tends to have a negative impact on the public’s perceptions of the legitimacy and performance of government, as well as trust in government. Instead, corruption is likely to increase the public’s willingness to break rules (Villoria et al., 2013).

For the past two decades, diverse anti-corruption measures have been developed and implemented across countries. Those measures can be categorized into three different but complementary approaches (Bertot et al., 2010; Jain, 2001; Shim and Eom, 2009): administrative reform; law enforcement; and social empowerment. The administrative reform approach aims to enhance the quality of bureaucracy because this approach considers bureaucratic rigidity and inefficiency as an important determinant of corruption. Thus, this approach stresses merit-based recruitment and promotion, professionalism, and performance management to reduce corruption in public administration (Jain, 2001; Shim and Eom, 2009). The law-enforcement approach aims to strengthen the criminal justice system because an effective criminal justice system increases the potential costs and punishments for corruption (Bertot et al., 2010). Oftentimes, the law-enforcement approach complements the administrative reform approach because the former increases the possibility of detecting corruption, while the latter reduces the opportunity of performing corruption (Rose-Ackerman, 1999). The social-empowerment approach stresses the importance of public involvement in policy decision-making and implementation processes (Johnston, 1998). Thus, this approach encourages the public to actively participate in the policy process and contends that such public involvement can help build “a civil, law-based society as a long-term deterrent to corruption” (Bertot et al., 2010: 265).

E-government

Initially, studies of e-government were interested in the use of ICTs regarding “the routine activities undertaken by public organizations” (Harrison et al., 2012: 85). Those routine activities pertain to the management of government information and the provision of public services to non-state stakeholders (Lee et al., 2011). In most cases, e-government initiatives aim to improve the efficiency, effectiveness, and quality of government operations and service delivery systems (Chadwick, 2003).

Recently, e-government scholars and practitioners have noted the importance of interactions between governments and non-state stakeholders (Abu-Shanab, 2015). Thus, the scope of the e-government literature is expanding by considering not only electronic service delivery and basic government operations, but also technology-enabled citizen participation and engagement (Lofstedt, 2005). Today, e-government is defined broadly as the use and application of diverse ICTs to manage government organizations, improve public service delivery systems, and expand interactions between governments and non-state stakeholders (Harrison et al., 2012; United Nations, 2014). In particular, studies on diverse technology-enabled citizen participation and engagement initiatives can mostly be found in the open government literature. Open government as one type of e-government oftentimes refers to “a multilateral, political, and social process, which includes in particular transparent, collaborative, and participatory action by government and administration” through ICTs (Wirtz and Birkmeyer, 2015: 382–384). Many scholars argue that open government consists of three pillars or phases: transparency; participation; and collaboration. Transparency refers to the timely provision of government information and data regarding the annual budget and expenditure, organizational performance reports, procurement data, and so on (Ganapati and Reddick, 2012). Participation refers to “the engagement and involvement of citizens in the decision making process utilizing ICT tools” (Abu-Shanab, 2015: 455). In the literature, the concept of participation is mainly understood as e-consultation. Thus, it means obtaining non-state stakeholders’ ideas, expertise, and opinions about policy problems and alternatives (Lee and Kwak, 2012; Longo, 2017). Collaboration indicates that governments and non-state stakeholders work together to solve complex social problems (Noveck, 2009). In this phase, non-state stakeholders more deeply engage in policy decision-making and implementation than in the earlier phases.

Importantly, many scholars argue that e-government can act as an effective anti-corruption tool (Cho and Choi, 2004; Wirtz and Birkmeyer, 2015). Indeed, several intergovernmental organizations, such as the World Bank and the United Nations (UN), have encouraged governments to adopt diverse e-government initiatives in order to curb administrative and political corruptions over the past decade.

Relationships between e-government and corruption

There are many examples of e-government being utilized to address corruption problems across the globe. For instance, in Brazil, an e-procurement system called Comprasnet was introduced to provide information about the price of outsourced services. This program enabled high-level public officials to monitor price fixing or inflation by corrupt officials (Shim and Eom, 2008). E-government can reduce corruption by transforming internal government routine activities and external relationships with non-state stakeholders in public administration (Shim and Eom, 2008). E-government initiatives like online service application systems reduce personal contacts between public officials and non-state stakeholders, thus curbing the discretion and arbitrary decisions of corrupt public officials (Cho and Choi, 2004). Also, these initiatives enable higher-ranked officials and audit staff to monitor corrupt public officials’ improper decisions and delays (Cho and Choi, 2004). Moreover, e-government initiatives for advancing citizen participation (i.e. open government) enable non-state stakeholders to access information about policy decision-making, implementation, and evaluation processes more easily, and to improve non-state stakeholders’ engagement in those processes (Relly, 2012; Shim and Eom, 2009). These initiatives can reduce the monopoly of state power, which is considered as one of the key drivers of corruption, and can enhance government transparency and accountability (Pathak et al., 2009).

Some scholars have sought to examine the relationships between e-government and corruption in quantitative and qualitative manners. This article reviewed 12 empirical studies that were published in peer-reviewed journals (see Table A1 online). Most scholars conducted quantitative macro-comparative research across countries (Andersen, 2009; Elbahnasawy, 2014; Garcia-Murillo, 2009; Krishnan et al., 2013; Lupu and Lazăr, 2015), while a few scholars focused on a specific case or country, including Fiji, Ethiopia, Mexico, or South Korea (Cho and Choi, 2004; Pathak et al., 2008; Valle-Cruz et al., 2016). Results of those studies indicate that there is a statistically significant negative relationship between the level of e-government and the level of corruption (Andersen, 2009; Shim and Eom, 2008). In addition, those prior studies show that the use of ICTs, including Internet adoption and mobile phone subscriptions, tends to reduce corruption (Relly, 2012; Shim and Eom, 2009).

Despite such evidence, this article notes several important limitations of the prior studies. First, from a methodological perspective, it seems that the prior studies could not provide enough evidence to support causal relationships between e-government and corruption because most prior studies collected cross-sectional data and then utilized correlation analysis and/or ordinary least squares (OLS) regression analysis. Those studies paid little attention to causal inference (Morgan and Winship, 2010). Next, most prior studies used data collected before 2010 for their analysis. Over the past 10 years, many novel ICTs, such as cloud computing, social media, and real-time collaborative writing, have been developed and adopted for online service delivery, communication, and collaboration between governments and non-state stakeholders. However, the prior studies did not reflect the adoption of those novel technologies. Also, the prior studies primarily concentrated on the relationships between corruption and electronic service delivery, and paid little attention to the effect of open government on reducing corruption, although the literature stresses the potential of open government as an effective anti-corruption tool (Bertot et al., 2010). Lastly, most prior studies did not take into account interactive effects between e-government and other determinants of corruption. Those prior studies simply sought to examine the direct effect of e-government on corruption but did not consider how other political, social, and technological factors influence the effects of e-government on corruption.

Theoretical framework and hypotheses

To fill the research gaps stated earlier, this article developed 10 hypotheses. The first two hypotheses intend to examine the direct effects of e-government as a whole and open government as one type of e-government on curbing corruption, controlling for political, societal, economic, and technological factors that have been considered as determinants of corruption in the literature. In this study, e-government is defined broadly as the use of ICTs by governments for internal and managerial activities, the production and delivery of public services, and enhancing relationships with non-state stakeholders in public administration (Harrison et al., 2012; Shim and Eom, 2008). Of diverse e-government initiatives, open government focuses mainly on relationships between governments and non-state stakeholders; thus, it refers to the use of technology by governments to provide information to non-state stakeholders, to obtain inputs from non-state stakeholders, and to co-create solutions to complex social problems (Wirtz and Birkmeyer, 2015). Corruption is defined as activities “in which the power of public office is used for personal gain in a manner that contravenes the rules of the game” (Jain, 2001: 73):

Hypothesis 1: If countries adopt and implement higher levels of e-government as a whole, their corruption levels will be reduced.

Hypothesis 2: If countries adopt and implement higher levels of open government, their corruption levels will be reduced.

This article also developed eight hypotheses to examine how political stability, the rule of law, telecommunication adoption, and levels of democracy moderate the effects of e-government as a whole and open government on corruption. These political, legal, and technological factors have been considered as important determinants of corruption (Dreher et al., 2007; Lio et al., 2011; Mauro, 1998). Political stability means that a regime maintains their political authority during a certain period of time and changes without unconstitutional or violent methods (Serra, 2006; World Bank, 2017b). According to the corruption literature, the level of political stability is negatively related to levels of corruption (Serra, 2006):

Hypothesis 3: The effect of e-government as a whole on reducing corruption will be greater in countries with higher levels of political stability than in countries with lower levels of political stability.

Hypothesis 4: The effect of open government on reducing corruption will be greater in countries with higher levels of political stability than in countries with lower levels of political stability.

Many scholars and practitioners have contended that the rule of law, which protects property rights and ensures the fairness and effectiveness of the criminal justice system, is an important determinant of corruption (Dreher et al., 2007). In particular, legal systems moderate the relationship between electoral accountability and corruption (Ferraz and Finan, 2011):

Hypothesis 5: The effect of e-government as a whole on reducing corruption will be greater in countries with more effective legal systems than in countries with less effective legal systems.

Hypothesis 6: The effect of open government on reducing corruption will be greater in countries with more effective legal systems than in countries with less effective legal systems.

Telecommunication adoption, including Internet adoption and mobile phone subscriptions, has been considered as a technological determinant of corruption (Elbahnasawy, 2014; Shim and Eom, 2009). Also, e-government and open government are highly dependent on telecommunication adoption:

Hypothesis 7: The effect of e-government as a whole on reducing corruption will be greater in countries with higher levels of telecommunication adoption than in countries with lower levels of telecommunication adoption.

Hypothesis 8: The effect of open government on reducing corruption will be greater in countries with higher levels of telecommunication adoption than in countries with lower levels of telecommunication adoption.

Lastly, the level of democracy, which promotes political competition and ensures government accountability, has been considered an important factor influencing corruption (Chowdhury, 2004; Dreher et al., 2007). In addition, scholars sometimes took democratic institutions into account as a moderator in the relationships between natural resource rents and corruption (Bhattacharyya and Hodler, 2010):

Hypothesis 9: The effect of e-government as a whole on reducing corruption will be greater in countries with higher levels of democracy than in countries with lower levels of democracy.

Hypothesis 10: The effect of open government on reducing corruption will be greater in countries with higher levels of democracy than in countries with lower levels of democracy.

Research methods

Data collection and measurements

Data were collected from various sources, including the UN and the World Bank, and the data span from 2003 to 2016. The unit of analysis is countries, and 214 countries are used in this study. The dependent variable, “corruption,” is measured by the control of corruption, which is from the World Governance Indicators (WGIs). The control of corruption measures the degree of perception of exerting public power for private benefits from the capturing of the state (World Bank, 2017b). It ranges from –2.5 to 2.5, with higher scores indicating lower levels of corruption; thus, we inversed the variable to interpret lower scores as indicating lower levels of corruption.

The main independent variable, “e-government,” is measured by the online service index from the UN e-government survey, which aims to assess the level of e-government as a whole, including online transactional services, open data portals, and e-participation initiatives (United Nations, 2016). It ranges from 0 to 1, with higher scores indicating higher levels of e-government. The other main independent variable, “open government,” as one type of e-government, is measured by the e-participation index from the UN e-government survey (United Nations, 2016). The e-participation index measures “the quality and usefulness of information and services provided by a country for the purpose of engaging its citizens in public policy through information and communication technologies” (Lee et al., 2011: 448). The e-participation index incorporates e-information, e-consultation, and e-decision making, and ranges from 0 to 1, with higher scores representing higher levels of e-participation.

Other independent variables, including voice and accountability, political stability, government effectiveness, regulatory quality, and the rule of law, are drawn from the WGIs (World Bank, 2017b). Voice and accountability measures the degree of perception of the selection of government through citizen participation, and it also measures the level of perception regarding freedom of expression, association, and media (World Bank, 2017b). Political stability measures the degree of perception regarding destabilization and overthrowing by unconstitutional methods (World Bank, 2017b). Government effectiveness measures the degree of perception regarding the quality of public and civil services, and policy formulation and implementation. Regulatory quality measures the level of perception of the government’s competency in formulating and implementing sound regulations (World Bank, 2017b). The rule of law measures the level of perception regarding the confidence of agents in complying with the rules of society, particularly in terms of contract enforcement, property rights, and the courts (World Bank, 2017b). All of the measurements range from –2.5 to 2.5, with a higher score indicating a higher level of voice and accountability, political stability, government effectiveness, regulatory quality, and the rule of law.

Human capital and telecommunication adoption are measured by the human capital index and the telecommunication infrastructure index, respectively, both from the UN e-government survey (United Nations, 2016). The human capital index incorporates the adult literacy rate and the combined primary, secondary, and tertiary gross enrollment ratio of the country, expected years of schooling, and average years of schooling (United Nations, 2016). The telecommunication infrastructure index is a composite measure that consists of estimated Internet users and the number of main fixed telephone lines, mobile subscribers, wireless broadband subscriptions, and fixed broadband subscriptions per 100 inhabitants (United Nations, 2016). Both measures range from 0 to 1, with a higher score indicating a higher level of human capital and telecommunication adoption.

Per capita GDP and population density are drawn from the World Bank database (World Bank, 2017a). The level of democracy is measured by the polity index under the Political Regime Characteristics and Transitions. The polity index is a combined, weighted measure that includes the competitiveness of political participation, the regulation and competitiveness of participation, the openness and competitiveness of executive recruitment, and constraints on the chief executive; it ranges from +10 (strongly democratic) to –10 (strongly autocratic) (Marshall et al., 2017). The data are drawn from the Center for Systemic Peace.

In analyzing the interactive effects between e-government as a whole and open government, on the one hand, and other political, legal, and technological factors, on the other, political stability, the rule of law, telecommunication adoption, and the level of democracy are coded as dummy variables based on the mean of each variable. That is, each value of those variables is coded 1 if it is greater than or equal to the means of respective variables, and it is coded 0 if less than the means.

Analysis

A fixed-effects model (FEM) for panel data analysis with clustered standard errors is conducted to examine the relationships between open government, e-government, and corruption.¹ The statistical software used for the analysis is STATA. Further, this article examined the standardized coefficients to compare the relative magnitudes of the independent variables on corruption.

Results

Table A2 (online) lays out the descriptive statistics, and Table A3 (online) provides the estimation results for the effects of e-government on corruption. Descriptive statistics show that there are missing data for every variable in the analysis. However, STATA can handle missing data by recognizing the data set as unbalanced panels. Thus, we applied fixed effects with unbalanced panels. Every model in the analysis shows that the R-squared is greater than 0.85 (see Tables A3, A4, and A5 online).

The coefficient of e-government turned out to be statistically significant and the direction of the relationship is negative, as expected in our main effect hypothesis 1. The coefficients of voice and accountability, government effectiveness, regulatory quality, and the rule of law are statistically significant, and there are negative relationships with levels of corruption in the e-government model. These results indicate that traditional factors appear to play a crucial role in reducing corruption. The coefficient of telecommunication adoption is statistically significant, but the direction of the relationship is positive, indicating that countries with higher levels of telecommunication adoption have higher levels of corruption.

The relative magnitude of the coefficients measured by standardized (beta) coefficients reveals that the rule of law tends to have a stronger impact on reducing corruption than other variables that have been traditionally regarded as anti-corruption factors. Meanwhile, the magnitude of the coefficients associated with e-government is relatively small in terms of reducing corruption, compared to other factors.

However, the coefficients associated with interactive effects between e-government, on the one hand, and political stability, the rule of law, telecommunication adoption, and the level of democracy, on the other, turned out to be statistically insignificant. These results fail to support our expectations (i.e. hypotheses 3, 5, 7, and 9), and suggest that these factors have an individual, direct impact on reducing corruption rather than having a moderating effect.

Table A4 (online) provides the estimation results for the impact of open government as one type of e-government on corruption. Similar to the results of the e-government model as a whole, the coefficients of voice and accountability, government effectiveness, regulatory quality, and the rule of law represent statistically significant negative relationships with the level of corruption in the open government model. There is also the impact of telecommunication adoption on corruption, in which the coefficient is statistically significant but the direction of the relationship is positive. In addition, the relative magnitude of the rule of law is also greater than those of other factors in terms of reducing corruption, which is similar to the results shown in the e-government model. However, the coefficient of open government turned out to be statistically insignificant. This result indicates that open government itself does not have a direct impact on corruption.

An interesting result is revealed in terms of an interactive effect between open government and the rule of law, in which the coefficient turns out to be statistically significant and the direction is negative, as expected in hypothesis 6. Thus, the rule of law not only has a significant direct impact on reducing corruption, but also serves as a moderator in the relationship between open government and corruption. This result implies that the effect of open government on reducing corruption would be greater in countries with more effective legal systems than in countries with less effective legal systems. Meanwhile, the moderating effects of political stability, telecommunication adoption, and the level of democracy in the relationship between open government and corruption are statistically insignificant.

Table A5 (online) includes both e-government and open government as anti-corruption strategies (i.e. an integrated model). The coefficient of e-government as a whole is still statistically significant even after the inclusion of open government, whereas the coefficient of open government as one type of e-government is still statistically insignificant. Similar with the results of the e-government model and the open government model, the coefficients of voice and accountability, government effectiveness, regulatory quality, and the rule of law turned out to be statistically significant and revealed negative relationships with the level of corruption in the integrated model. Also, there is a similar effect of telecommunication adoption on corruption, in which the coefficient is statistically significant but the direction of the relationship is positive.

We also conducted the pooled OLS estimation with time fixed effects (see Tables A6, A7, and A8 online). Compared to the results from panel data analysis, the distinct difference is that the coefficient of open government is statistically significant and the direction of the relationship is negative. Results from the pooled OLS estimation also indicate that open government would be an effective policy tool to reduce corruption (see Table A7 and A8 online).

Discussion

This article focused on e-government as an anti-corruption tool and aimed to test the impacts of e-government as a whole and open government as one type of e-government on reducing corruption. The study collected longitudinal data from 2003 and 2016 across 214 countries and then employed an FEM as a data analysis method. The study tested two main hypotheses regarding the direct effects of e-government and open government on curbing corruption, and also developed eight additional hypotheses to examine how political stability, the rule of law, telecommunication adoption, and the level of democracy moderate the effects of e-government and open government on reducing corruption.

The results of this study revealed that e-government as a whole has a significant and direct impact on reducing corruption, while open government as one type of e-government is dependent on the rule of law to reduce corruption. These results confirm that e-government can be an effective anti-corruption measure, but open government is unlikely to be effective in curbing corruption by itself. The findings from the research support the results of prior studies that employed quantitative research methods and found an impact of e-government on reducing corruption (Andersen, 2009; Garcia-Murillo, 2009; Shim and Eom, 2008), as well as those of qualitative case studies that explored the relationship between e-government and corruption (Cho and Choi, 2004).

An interesting finding from this study is that levels of telecommunication adoption are positively related to levels of corruption. According to the literature, there are negative relationships between cellular phone use/Internet adoption and corruption (Relly, 2012; Shim and Eom, 2009). However, the results of the research, which imply significant positive relationships between telecommunication adoption and corruption, are different from those of prior studies that empirically examined the relationships between technology and corruption (Elbahnasawy, 2014; Relly, 2012; Shim and Eom, 2009).

Conclusion and direction for future research

This research has several important theoretical and practical implications. First, analysis results support the argument that e-government is an effective tool to curb corruption. This study also extends the literature that paid little attention to the difference between the direct and indirect effects of e-government on corruption. Most previous studies took into account only the direct effect of e-government. However, this study revealed that open government as one type of e-government tends to have no direct effect on corruption. Open government has an interactive effect on curbing corruption, relying on the rule of law, which acts as a moderator in the relationship between open government and corruption. Also, e-government appears to have less effect on reducing corruption than other administrative, political, and legal factors do (i.e. government effectiveness, regulatory quality, and the rule of law). Thus, from a practical point of view, a combined approach to anti-corruption that utilizes both e-government initiatives and other anti-corruption tools may be more effective in reducing corruption than over-reliance on e-government initiatives.

Importantly, as stated earlier, this research found evidence that higher levels of technology adoption may increase corruption. This may mean that advanced ICTs can be used for performing corruption rather than detecting and reducing it. However, those negative impacts on corruption may perhaps be likely to occur soon after e-government systems are newly adopted (Bhatnagar, 2003). Thus, further research is required to examine the direct and indirect effects of technology adoption on corruption.

This study has several limitations. First, this research did not take into consideration global initiatives established by intergovernmental organizations for the reduction of corruption, such as the UN Convention against Corruption, although this research sought to control for diverse political, social, legal, and technological factors at the national level. Thus, future research needs to consider those kinds of global initiatives. Next, this study did not consider lagged effects of e-government and open government on corruption because this study employed an FEM. In particular, according to the literature, open government initiatives based on a citizen-engagement approach tend to take time to reduce corruption (Relly, 2012). Thus, scholars need to conduct empirical research on delayed changes in levels of corruption caused by e-government and open government. Also, different levels of maturity in education and economy at the national level may moderate the relationships between e-government and corruption (Kolstad and Wiig, 2009). However, the research did not take into account educational and economic factors as moderators. Therefore, further research is needed to examine how those factors influence the impacts of e-government on corruption. Additionally, although this study found empirical evidence on the impacts of e-government on curbing corruption, the interpretation of those findings may be limited because the research used aggregated indexes to measure variables. Thus, additional research would be useful to make more practical recommendations on how to develop strategies for the adoption of e-government in order to reduce corruption.

Supplemental Material

Supplemental material for E-government as an anti-corruption tool: panel data analysis across countries

Supplemental Material for E-government as an anti-corruption tool: panel data analysis across countries by Chul Hyun Park and Koomin Kim in International Review of Administrative Sciences

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Supplemental material

Supplemental material can be found at: journals-sagepub-com.web.bisu.edu.cn/home/ras

Note

Chul Hyun Park is an Assistant Professor at the University of Arkansas Clinton School of Public Service (UACS), USA. Regarding his research, he has been interested in open and collaborative governance between government and non-state stakeholders. He has conducted research on emerging technologies that enable multiple actors across the public, nonprofit, and for-profit sectors to effectively communicate and collaborate with one another in order to collectively resolve complex social problems. He received a PhD in Public Administration and Policy from Arizona State University and a Master’s of Public Policy from Georgia State University.

Koomin Kim is a Postdoctoral Researcher at Florida State University, USA. His research has focused on policy innovation and diffusion, comparative policy, state and local budgeting and financial management, policy process theories, global and US tax policy, and open government. He received a PhD in Public Administration from Florida State University and a Master’s of Public Administration from Arizona State University.

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