Green Economy - the Engine of Economic Growth and Development in Romania in the Context of Climate Change

In recent years, the issue of climate change management has been intensely debated as a subject of national interest, as extreme weather events have had negative effects on Romania through significant economic losses in most industrial sectors. In the context of a negative scenario of increasing global warming, the economic situation of the country, under the impact of climate change, would deteriorate significantly. However, as a responsible member of the European Union and the global community, Romania contributes to harnessing the opportunities for gains from active climate change management by increasing the expansion and efficient use of resources that will improve competitiveness, by green technologies and practices that will reduce local pollution, and by resilient approaches to climate change that will protect against weather-related risks. Resilient and adaptive measures by the state to manage the impacts of climate change can generate inclusive, green and long-term growth in the state’s economy, resulting in improved human well-being and social equality

Tackling Climate Risks: Current Strategies for Monitoring and Preventing Climate Hazards

The Paris Agreement's signatories submitted in 2021 their updated climate action targets and commitments, known as Nationally Determined Contributions (NDCs). These goals encompass the efforts that countries will make in the next few years to reduce emissions and improve resilience. Meteorological and climatic products are a significant tool in climate risk management and adaptation to climate variability. In order to build resilience for sustainable development, both climate change and extreme weather occurrences must be incorporated into risk assessments. The goal of this research is to highlight the key approaches used by the world's major countries for monitoring and preventing climate hazards. Furthermore, the main actions implemented by Romania are taken into account. We will also explore a potential link between climate risks in the context of online commerce and the redefinition of global business models

A Projection Approach of Tourist Circulation under Conditions of Uncertainty

This paper explores an important problem in tourism demand analysis, namely, the inherent uncertainty involved in projecting tourism demand. Tourism demand continues to be severely affected by unforeseen events associated with the current global health crisis, which has led to an examination of ways to predict the devastating effects of the COVID-19 pandemic on tourism. Tourism flow forecasting relating to arrivals is of particular importance for tourism and the entire hospitality industry, because it is an indicator of future demand. Thus, it provides fundamental information that can be applied in the planning and development of future strategies. Accurate forecasts of seasonal tourist flows can help decision-makers increase the efficiency of their strategic planning and reduce the risk of decision-making failure. Due to the growing interest in more advanced forecasting methods, we applied the ARMA model method to analyze the evolution of monthly arrival series for Romania in the period from January 2010 to September 2021, in order to ascertain the best statistical forecasting model for arrivals. We conducted this research to find the best method of forecasting tourist demand, and we compared two forecasting models: AR(1)MA(1) and AR(1)MA(2). Our study results show that the superior model for the prediction of tourist demand is AR(1)MA(1)

A Statistical Analysis of the Migration Process: A Case Study—Romania

The research aims at studying and predicting the migration process in Romania over the last 20 years and at identifying the impact of the COVID-19 pandemic. The study analyzes several models for estimating migration through linear regression, but also a VAR (Vector autoregression) analysis, as the variables can influence each other. Vector autoregression (VAR) is also used to model multivariate time series, and it can analyze the dynamics of a migration process. Therefore, the best model for forecasting the migration process in Romania is Model 1 of linear regression. This phenomenon generates many positive and negative economic, demographic and political effects. The migration process has become particularly important for Romania in the last 20 years, and its socio-economic, political and cultural effects affect the Romanian state. That is why flexible policies are needed in order to be coherent, to have as main purpose keeping specialists in the country in certain basic economic fields, as well to implement measures to determine the return of specialists and students who have left to study abroad

A Statistical Analysis of the Migration Process: A Case Study—Romania

The research aims at studying and predicting the migration process in Romania over the last 20 years and at identifying the impact of the COVID-19 pandemic. The study analyzes several models for estimating migration through linear regression, but also a VAR (Vector autoregression) analysis, as the variables can influence each other. Vector autoregression (VAR) is also used to model multivariate time series, and it can analyze the dynamics of a migration process. Therefore, the best model for forecasting the migration process in Romania is Model 1 of linear regression. This phenomenon generates many positive and negative economic, demographic and political effects. The migration process has become particularly important for Romania in the last 20 years, and its socio-economic, political and cultural effects affect the Romanian state. That is why flexible policies are needed in order to be coherent, to have as main purpose keeping specialists in the country in certain basic economic fields, as well to implement measures to determine the return of specialists and students who have left to study abroad