Slovak Republic


Improving Corruption Risk Management in the Slovak Republic

Results from a 2023 Experiment in Applying Behavioural Insights to Public Integrity

This report provides insights on applying behavioural insights to improve public integrity in the public administration of the Slovak Republic. This report illustrates, through a stepwise application of the OECD BASIC toolkit, how corruption risk management policies can be improved through the identification and analysis of undesired behaviours, and through the design and testing of strategies to change these behaviours. Specifically, a randomised controlled trial was employed to test the effect of two behaviourally informed strategies to improve risk communication in the public administration. The results provided novel empirical evidence that: 1) providing support to public servants to better understand risks; and 2) exposing public servants to good leadership examples can improve their propensity to communicate risks. Moreover, it was found that feeling safe, trusting and being aware of risk communication channels also play an important role in improving risk communication. Based on the findings, this report provides recommendations to improve the risk management system of the Slovak Republic and inform the discussion on the upcoming National Anti-corruption Strategy, contributing to advancing the country’s efforts in curbing corruption.

Published on April 20, 2024

In series:OECD Public Governance Reviewsview more titles


Executive summary
Behavioural analysis and proposals to strengthen corruption risk management in the Slovak Republic
Experimenting and assessing the impact of two behavioural strategies in the Slovak Republic
Lessons to strengthen corruption risk management in the Slovak Republic
Annexes16 chapters available
Online vignette experiment-survey script (in English)
Emails to disseminate the survey
Distribution of the primary outcome variable
Distributions of logarithmic and non-logarithmic values of age and years in public administration
The results from the OLS regression, dependent variable: likelihood of communicating a risk
Plots for the normality of residuals
Test for heteroskedasticity
Tests for Logit-regression
Tests for Tobit-regression
Regression to show the effect of agencies
Regression to test interactions between treatments and covariates
Regression output, dependent variable: likelihood of communicating a risk (with rounded frequencies)
Box plot of the likelihood of communicating a risk with jitter
Regression to test interactions between hiring responsibility and knowledge on reporting channels
Descriptive statistics of the three study groups, and the total sample by treatment group.
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