## 6 Empirical Results
\begin{table}
\begin{tabular}{l l l} \hline \hline
**Code** & **KPI** & **Unit** \\ \hline CC & Contribution to climate-related spending & Million euro \\ CC\_E & Control of corruption: estimate & Number \\ EE & Unemployment expenditure & Euro/inhabitant \\ VA\_E & Voice and accountability, freedom of expression: estimate & Number \\ GDP\_PC & GDP/capita & USD \\ EH & Expenditure on Sickness/healthcare and disability & Euro/inhabitant \\ PCCEB & Population with confidence in EU institutions & Percentage \\ GE\_PR & Governance effectiveness: percentile rank & Percentage \\ RC & Recycling of batteries and accumulators, cadmium content & Tone \\ EHS & Housing and social exclusion expenditure & Euro/inhabitant \\ ET1 & Final energy consumption in transport by type of fuel (gas and diesel oil) & Number \\ IPS & E-government activities of individuals via websites & Percentage \\ RL\_E & Rule of low: estimate & Number \\ zeroEV & Total number of electricity, hydrogen, and fuel cells passenger cars & Number \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Selected KPIs. of the 57 KPIs was evaluated, identifying the ten most relevant. Figure 5 shows the most important KPIs and their relative percentage of importance. Some of the KPIs that stand out are GDP per capita (GDP_PC), corruption perception index (CP), and contribution to the international commitment of USD 100 billion in climate-related expenditures (CC), which have the highest impact on cluster formation compared to the other KPIs. Figure 6 shows the distribution of the countries within each cluster. The bar chart on the left illustrates the number of countries in each cluster, while the pie chart on the right displays the percentage distribution. Cluster 0 contains 14 countries, representing 46.9% of the total. Cluster 1 comprises 10 countries, accounting for 34.4%. Cluster 2 has 4 countries, making up 12.5%, and Cluster 3 consists of 2 countries, representing 6.2% of the total. Figure 7 shows the projection of the countries in a two-dimensional space using PCA. This representation allows visualizing the dispersion and grouping of the countries according to the identified clusters. The axes of the graph represent the first two principal components, which explain most of the variability in the data. Cluster 0 includes 15 countries mainly from Central and Eastern Europe, such as Bulgaria, Czech Republic, Greece, Croatia, Cyprus, Latvia, Lithuania, Hungary, Malta, Portugal, Romania, Slovenia, Slovakia, Albania and Serbia. These countries present characteristics of moderate development. GDP per capita values vary, with urbanization levels reflecting progress toward modernization. Indicators of access to drinking water and sanitation are also diverse, with some countries reaching almost full coverage, while others are still developing. Expected years of education and governance levels show moderate values, suggesting areas for improvement in infrastructure and public services. Figure 5: The top ten important KPIs in clustering. Cluster 1 groups 11 mostly Northern European countries, including Belgium, Denmark, Estonia, Ireland, Luxembourg, the Netherlands, Austria, Finland, Sweden, Iceland and Norway. These countries stand out for having the highest GDP per capita and the best rates of government effectiveness. They have high levels of urbanization, almost uni  
Figure 6: Count of the countries in each cluster. Figure 7: Defined clusters with respect to two principal components. versal access to water and sanitation, and the highest expected years of education. These indicators reflect advanced economies with solid infrastructure and high living standards. Cluster 2 consists of 4 countries: Spain, Italy, Poland and Turkey. These countries have the second-highest levels of GDP per capita and expected education. Although largely urbanized, they show variations in other social and economic indicators. Access to drinking water and sanitation is high but does not reach the near-universal levels observed in Cluster 1.