Digital Readiness of European Countries to Combat Corruption and Cyber Threats: Panel Analysis

In today’s world of globalization and digital transformation, issues of transparency, security, and effective governance are becoming increasingly important. Corruption and cybercrime remain serious challenges for many countries around the world. These phenomena undermine trust in state institutions, hamper economic development, reduce investment attractiveness, and affect social justice. This paper aims to model the impact of digital technologies on the readiness of 28 European countries to combat corruption and cybercrime over the period 2012‒2024. The results of the statistical analysis show that the highest variability is observed in indices related to corruption, while indicators related to digitalization and economic freedom exhibit the least variability. Pooled OLS regression, fixed effects regression, and random effects regression were employed for modeling. The Breusch-Pagan LM test, F-test, and Hausman test confirmed the significance of fixed effects in determining the digital readiness of countries to counter corruption and cyber threats. These models allowed for assessing each country’s deviation from the average level, controlling for other variables. Countries with statistically significant positive fixed effects, such as Denmark, Sweden, Finland, the Netherlands, and Germany, demonstrate a high level of digital readiness to combat corruption. Conversely, negative effects were observed for Italy, Portugal, Spain, and the Czech Republic. Fixed effects by year indicate a decline in the index in 2022 and an even greater drop in 2024, suggesting a worsening perception of corruption in recent years. The fixed effects model confirms that institutional characteristics remain key factors influencing corruption perception. It has been established that digital indicators are not independent determinants and can only be effective when supported by a strong institutional framework. The results of the fixed effects regression model assessing network readiness to counter cyber threats also indicate the robustness of the constructed model. Among the main independent variables, the number of Internet users and the Corruption Control Index were found to be statistically significant. As the number of Internet users increases, so does the state’s overall level of digital readiness. A higher level of corruption control contributes to improved digital infrastructure and its public perception. At the same time, the Economic Freedom Index and the Government Restrictions Index were not statistically significant in this model. The e-Government Development Index showed a positive effect, although its p-value slightly exceeds the traditional significance threshold, indicating that its influence is close to statistically significant. Sweden, the Netherlands, Finland, Germany, and Denmark demonstrated statistically significant positive effects, indicating a high level of digital readiness to counter cyber threats. In contrast, countries such as Greece, Croatia, Romania, Poland, Slovenia, Bulgaria, Portugal, Spain, and Hungary exhibited statistically significant negative effects. An analysis of fixed effects by year reveals a substantial decline in the network readiness index in 2024. A negative effect was also observed in 2022, although it was not statistically significant. The findings can be used to formulate recommendations for enhancing cybersecurity and anti-corruption policies within the context of digital transformation.