Perceived Corruption in Light of Green Transition Indicators

• Published in: RGSA : Revista de Gestão Social e Ambiental 2024-07, Vol.18 (3), p.e07855
• Main Authors: Kálmán, Botond Géza, Malatyinszki, Szilárd, Zugor, Zsuzsanna, Szőke, Brigitta
• Format: Article
• Language: English
• ISSN: 1981-982X; 1981-982X
• DOI: 10.24857/rgsa.v18n3-166

Objective: The aim of the study is to investigate how the areas of the green transition that promote sustainability relate to perceived levels of corruption.   Theoretical Framework: The variables of corruption, economic growth, renewable energies and carbon dioxide emissions are integrated together in the long run. There is a causal relationship between carbon dioxide emissions, corruption, economic growth and renewable energies. The corruption index and economic growth have a statistically significant relationship with carbon dioxide emissions. However, the impact of renewable energies and international trade slows climate change and improves the quality of the environment.   Method: We based our research on publicly available internet databases. The data available here can be freely used. This means that no matter what questionnaire they are based on, their analysis does not require a research permit. Another advantage of such databases is that the research conducted using them can be reproduced and continued in the future. We modeled the level of corruption using the time series of Transparency International's Corruption Perceptions Index. We examined the countries that are included in both databases. After cleaning and coding data the first step was to create descriptive statistics. At the same time, the normality of the sample was tested and the homoscedasticity condition was checked, because these two latter tests determine which statistical methods can be used for the purpose of further investigations. This was followed by the examination of the question, to what extent and in what direction environmental indices influence Corruption perception. For this purpose, we made a correlation matrix. Based on it we created a regression model in which the CPI was the dependent (explanatory) variable and the environmental indices were included as independent (explanatory) variables.   Results and Discussion: Corruption prevention is significantly influenced by Environmental policy, Particulate matter and Gross greenhouse gas emissions - the latter has a negative effect. The increase in waste generation also reduces the CPI, thus increasing the feeling of corruption, but this effect did not prove to be significant. In addition, recycling is an important marketing factor of the Corporate Social Responsibility (CSR) policy. Therefore, in some ways, it is more valuable than money. There is a correlation between the perceived level of corruption and environmental