Over time, the concept of economic development has been the cause of debates in the research environment. Some of the researchers consider the level of economic development of a country to be characterized by high levels of the main macroeconomic aggregates, while another part supports the idea of uniform economic development with a high level of social inclusion. Regardless of the definition of the concept of economic development, it has been proven that a major positive impact is generated by the sustainable development strategy, especially in the light of the concept of circular economy. Therefore, the study addresses the level of economic development of the member states of the European Union based on the impact generated by the circular economy. In addition, based on the analysis carried out, the paper aims to identify the dependency ratio between the variables associated with the circular economy concept and the level of economic development. In order to achieve these goals, a panel regression model was estimated, for all member states of the European Union, on the time horizon 2011-2020. The model used as dependent variable “the level of economic development”, and the independent variables were made up of variables associated with the circular economy. The results of this analysis reveal that there are individual effects on both dimensions associated with the analysis (cross-sectional, time series), which leads to the idea that each country is influenced in the process of economic development through the circular economy by its own specificities.

The circular economy has increasingly attracted the attention of regulators as a result of the emergence of the challenges associated with climate change and the need to increase the lifetime of goods in order to reduce waste and high consumption of resources. Therefore, the paper aims to identify the current state of the circular economy in Romania by analyzing waste recovery in territorial profile. Also, another objective of the work is to identify the gaps in the territorial profile of the recovery rate of collected waste. To achieve the goals of the research, appropriate statistical methods were used in this study, such as: the Jenks algorithm and the Gini Coefficient. The main results of research suggest there are a lot of gaps in territorial profile from recycling rate perspective and a low concern about circular economy in Romania.

Nowadays, the renewable energy sector is an area of interest for every state. Global regulations and policies encourage the development of these technologies, given the current political context, but also environmental issues. Romania, due to its geographical position and climate, is considered a country with high potential regarding the implementation of alternative sources of renewable energy. This research presents the importance of solar energy and provides a statistical analysis on the sectors influencing the implementation of green energy. At the same time, those counties that are eligible are identified and different scenarios are created for the ineligible counties that lead to their eligibility. The research develops 3 main objectives. To begin with, it is desired to be created an overview of the indicators included in the analysis, in order to develop a detailed statistical analysis of the situation of each county of Romania. Following this extracted information, the second objective is outlined, which is to create an indicator that groups counties into counties eligible for solar energy and counties ineligible for solar energy using the K-Means Cluster-unsupervised learning algorithm. Finally, using the supervised learning algorithm - Logistic Regression, predictions will be made with the help of which those sectors of activity that can be improved in order to implement green energy will be identified.