# Evaluation of Sustainable Development in European Union Countries
## 5 Results
### Results  
Given the number of countries to be analyzed, it was decided to classify the alternatives of the model depending on their geographical situation. They were categorized into four regions: Northern, Western, Eastern, and Southern Europe (see Figure 10). \begin{table}
\begin{tabular}{c c c} \hline \hline \multirow{2}{*}{**Subcriterion**} & **Number of Negative** & **Justification** \\  & **Data Points** & \\ \hline SED-SRH & 33 & \begin{tabular}{c} Makes sense. Negative savings rate shows that households have \\ more expenses than income. \\ \end{tabular} \\ \hline SCP-EMA & 8 & \begin{tabular}{c} Does not make sense. The number of companies respectful of \\ the environment cannot be negative. \\ \end{tabular} \\ \hline DCH-ANM & 112 & \begin{tabular}{c} Makes sense. As the migration rate is described, the negative \\ values indicate more emigration than immigration, and the \\ positive values more immigration than emigration. \\ \end{tabular} \\ \hline PHE-UMN & 1 & \begin{tabular}{c} Does not make sense. It is a parameter that indicates the \\ percentage of people with unmet medical needs, and as such its \\ value cannot less than zero. \\ \end{tabular} \\ \hline CCE-EDE & 19 & \begin{tabular}{c} Makes sense. Negative values of energy dependence suggest \\ that the country imports energy to meet its needs. \\ \end{tabular} \\ \hline GAD-ODA & 5 & \
\begin{tabular}{c} Does not make sense. This parameter expresses the aid and \\ loans given by the EU with respect to the gross domestic \\ product of the country. \\ \end{tabular} \\ \hline GAD-EDF & 13 &
\begin{tabular}{c} Makes sense. Negative values of funding suggest that the \\ country receives less credit than it has to pay back in that period. \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 17: Identification of negative measurements. Once the scaled matrices have been found, an AHP analysis is carried out for each period, introducing the weightings and value matrices in the _Expert Choice_ software. This tool gives its judgements by percentages through relative assessments, where the alternative of greatest sustainability is the one whose percentage is highest, and a ranking is created between them. However, this is a handicap for the analysis of the evolution over time, since it is not possible to control whether all the alternatives increase or decrease their real sustainability in the same period. Applying the AHP methodology to all the periods gives an evolution over time of the sustainability of each of the alternatives. Figure 11 shows the resulting assessments for the countries for each period, classifying the results by the geographical area they belong to. Analyzing the results, it is possible to classify the alternatives into different sustainability rankings, and so they are then categorized by their geographical area:  
1. Northern European area: this area shows a higher average than the others; it can be seen that Norway is the country with the highest SD, and an intermediate group with Sweden and Iceland. Figure 10: Differentiation of the alternatives by geographical region. In addition, the evolution of Finland is very clear, starting at the lower level and finishing at the intermediate, and of Denmark, which starts at the higher level and ends at the intermediate. The variation of the Northern countries in terms of SD in 2015 with respect to 2005 shows a mean value of \(-0.02\), essentially due to the decline of Denmark. 2. Western European area: three levels of sustainability can be discerned, a lower one that includes Ireland, a medium level comprising Belgium, Germany, France, Luxembourg, Austria, and Czech Republic and a higher level where the Netherlands stands out at the alternative with greatest sustainability, followed by the United Kingdom. Looking at the variation of the countries in SD in 2015 with respect to 2005, we find a mean of 0, since the great increase of the Czech Republic balances the small declines of Belgium, France, Luxembourg, the Netherlands, and Austria. 3.