Green projects risk assessment models

• Дата: 2024
• Автори: Кузнєцова, Н. В., Шевчук, О. С.
• Формат: Стаття
• Мова: Ukrainian
• Опубліковано: Інститут проблем реєстрації інформації НАН України 2024
• Теми: green projects; risk assessment; methodology; logistic regression; decision trees
• Онлайн доступ: http://drsp.ipri.kiev.ua/article/view/308752
• Назва журналу: Data Recording, Storage & Processing

The study is devoted to the analysis and forecasting of green projects investment and credit risks. The peculiarity of such projects is their ecological orientation. The assessment of their risks needs an ana-lysis of both economic and ecological components. The work researches existing approaches, methods and risk assessment models, both for the classic, purely economic case, and as well with environmental component. The existing classic methods of risk assessment are considered and their advantages and disadvantages are noted. Techniques for collecting, analyzing and combining data sets of economic and environmental indicators are proposed. Through modeling on the obtained data, the effectiveness of applying various methods such as: logistic regression, decision trees, random forest, AdaBoost and Extra Trees for risk assessment was shown for the case of economic and environmental data analysis. The simulation results have demonstrated that the application of classical assessment methods taking into account the ecological component is possible and the effectiveness of such forecasting will be sufficiently high. The idea of developing specialized approaches to assessing the green projects risks taking into account a wide range of identified factors is proposed. For investment and lending it will be possible to take into account not only the impact of carbon emissions, but also other types of pollution, which will allow by implementing green projects to improve the environmental situation of the world ecosystem as a whole. Tabl.: 5. Refs: 21 titles.