# Are Green Buildings an Indicator of Sustainable Development?
## 1 Introduction  
According to the International Monetary Fund, the Gross Domestic Product (GDP) measures the monetary value of goods and services produced in a region in a defined period [1]. Typically, its growth does not consider the environmental degradation of the resources adopted to achieve it. For this reason, effective economic growth represents the highest possible growth of GDP obtained by meeting the restrictions imposed by environmental protection [2]. Accordingly, sustainable development is seen as the fulfilment of present needs without compromising the ability of future generations to meet their own needs [2]. From the perspective of the scope of this paper, the most important goal is the growth of GDP with a simultaneous reduction in Greenhouse Gas (GHG) emissions, which is the most common indicator used to express environmental degradation [3] since GHGs (e.g., water vapor, carbon dioxide, methane, nitrous oxide, etc.) trap heat causing global warming once they are released into the atmosphere. One of the models that represent the link between economic growth and GHG emissions is the Environmental Kuznets Curve (EKC), which illustrates that the relationship between environmental degradation and GDP has an inverted U-shaped form, as seen in Figure 1[4]. The curve shows that a developing region is characterised by an initial fast economic growth that typically goes along with an increase in environmental degradation. The advances in the region generally lead to the development of new technologies that reverse the trend of the graph. From the turning point, the economy continues to grow together withenvironmental improvement, as shown by the decrease in GHG emissions [4]. Therefore, GDP is seen as both the cause and the cure for environmental degradation [5]. A study [6] develops the allometric regression line of the global annual anthropogenic CO\({}_{2}\) emissions as predicted isometrically by the global GDP. The statistical method introduces the R\({}^{2}\), an indicator that represents the proportion of the variance for a dependent variable (in this case, GDP) that is obtained from an independent variable (in this case, CO\({}_{2}\) emissions) in the regression model. However, the study [6] only considers the anthropogenic industrial and domestic emissions of goods and services but does not analyse the origin of the emissions. Globally, the GDP regression as a function of CO\({}_{2}\) emissions is characterised by a consistent R\({}^{2}\), valid also during COVID-19 lockdowns where the global GDP and CO\({}_{2}\) emissions dropped, respectively, by 7% and 7.29% [7]. Another study [8] assessed the relationship between GDP and GHGs to check the validity of the EKC curve in the European Union (EU), Norway and Switzerland between 1995 and 2010 using the data taken from the Eurostat database [8]. In addition to R\({}^{2}\), the \(p\)-value is introduced to explain the probability of obtaining results as extreme as the observed results of a statistical hypothesis test. The lower the \(p\)-value, the greater the statistical significance of the observed difference. However, the results of the assessment [8] show that in some cases, the model does not yield any significant results because R\({}^{2}\) values are very small and the \(p\)-value is too big. In 2015 the United Nations Member States adopted the 2030 Agenda for Sustainable Development, which states that growth must balance social, economic and environmental sustainability [9]. At its heart are the 17 Sustainable Development Goals (SDGs), which are an urgent call for action by all countries--developed and developing--in a global partnership to tackle several issues [10]. The share of the world's population in developing countries (e.g., China, India, South America, etc.) is bigger than the one in developed countries (e.g., North America, Europe, Japan, Australia, etc.) [11]. This, together with the constant urbanisation process, has been defined as the most important cause of the continuous growth of global GHG emissions [11].