The determinants of corruption at the individual level: evidence from Bosnia-Herzegovina

Abstract

This article uses data from the National Survey of Citizens' Perceptions in Bosnia-Herzegovina to investigate the determinants of offering a bribe in the form of money, gifts or services to medical personnel, professors, judicial personnel, police officers and public servants. We presented evidence about the spread of corruption in these five sectors of the economy in Bosnia-Herzegovina, and analysed the effects of determinants at the individual level on the likelihood of engaging in bribery. Our results confirmed that specific personal characteristics predicted corrupt behaviour, but results varied across sectors. Logistic regression was used to generate models from which predictions could be made about the likelihood of an individual engaging in corrupt behaviour. Our research shows that corruption is a widespread phenomenon in Bosnia-Herzegovina, and more educated people, people living in urban areas, and individuals with higher incomes are more likely to engage in bribery in several sectors. Measures and policies aimed at reducing corrupt behaviour should be designed in a way that considers the specific characteristics of these individuals.

Public Sector Strategies in Curbing Corruption: A Review of the Literature

“…Considering the results of the review, several authors have recently addressed the determinants of corruption at the individual level. Among others, Mangafić and Veselinović (2020) analyzed the effects of individual determinants on the likelihood of engaging in bribery, confirming that specific personal characteristics predicted corrupt behavior. Rabl (2011) explores the effect of contextual variables on the willingness of the individual to accept a bribe using laboratory experiments.…”

Local Development Planning in Nepal: Does it Actually Reflect Citizen Participation?

“…The slope measures the ratio of the likelihood of participation in development planning and discussion to the likelihood of non-participation in development planning and discussion in relation to each reference group. In this analysis, the odds ratio is stated because it offers a more instinctual way of interpreting effects (Mangafic & Veselinovic, 2020). Required statistical information was generated from the SPSS version 26, and data were tabulated and then analysed with the help of appropriate literature on citizen participation.…”

Machine learning prediction of petty corruption intention among law enforcement officers

“…According to a review of the literature on corruption, most previous research relied on correlations and regression-based statistical techniques [15], [16]. Nevertheless, recently, the use of artificial intelligence and machine learning approaches in identifying and comprehending governmental fraud and corruption has gained traction in the literature [13], [14], due to its ability to discover trends and patterns in a wide range of data [13].…”

“…Six machine learning algorithms namely generalized linear model, fast large margin, decision tree, random forest, gradient boosted trees, and support vector machine were used to be executed in a 16 suggested, and the optimal hyper-parameters setting are given in Table 3. Not available (NA) denotes that the algorithm is not using the given parameters.…”