1 Introduction
2 Method
2.1 Factorial Analysis
2.2 Principal Component Analysis and Correlation Matrix
3 Analysis and Discussion of the Results
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The communities in the area with the best results contain 15.06% of the total population as opposed to the worst-rated communities, which accumulate 31.73% of the Spanish population.
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The concentration of cities with the worst results coincides with the areas with the highest tourist concentration on the Iberian Peninsula.
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The territories with the best Sustainable Development results are among the most affected regions by the abandonment of the population of their municipalities.
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Average population density measured in inhabitant per km2.
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Median age of the population measured in years.
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Population measured in number of inhabitants.
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Total number of households measured in absolute values.
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Rate of employment in industry measured as a percentage of total employees.
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Rate of employment in services measured as a percentage of total employees.
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Rate of foreign-born individuals as a percentage of the total population.
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Employment rate of people between the ages of 20 and 64 measured as a percentage of the working population.
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Rate of population over 65 years measured as a percentage of the total population.
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Rate of population between the ages of 0 and 14 measured as a percentage of the total population.
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Average annual net income per capita measured in euros per capita.
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Surface measured in km2.
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Average household size of the municipality measured in number of inhabitants per household.
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Gross mortality rate.
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Unemployment rate.
Component | Squared charge extraction sums | ||
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Total | % Variance | % Accumulated | |
1 | 3439 | 20,232 | 20,232 |
2 | 2339 | 13,759 | 33,991 |
3 | 1778 | 10,461 | 44,452 |
4 | 1495 | 8797 | 53,248 |
5 | 1388 | 8165 | 61,414 |
6 | 1196 | 7034 | 68,448 |
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This is reflected through the correlation matrix since correlations are generally low (Table 2). The highest correlations are observed between SDG 12 and SDG 8 (0.57) and between SDG 13 and SDG 3 (0.52). These results differ from the most significant relationships in terms of synergies found in the UN meta-study (Singha et al. 2018). The interpretation of the second correlation is interesting and can be useful because better results in climate change management are associated with better health indicators. This conclusion is consistent with numerous international reports (Patz et al. 2005; UNFCCC 2017). Another powerful correlation associates the indicator of responsible consumption, SDG 12, with wealth sharing, SDG 10, and less unemployment, SDG 8. Other interesting correlations occur between SDG 17 and SDG 4 (0.41) and SDG 17 and SDG 12 (0.47). This new relationship complements those found in the UN meta-study (UN 2019).
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The SDGs with the lower correlations, and therefore more independent of the rest, are SDG 6 and SDG 14; even among them, the correlation is very low. Their relationship with the rest of the SDGs is almost non-existent. This conclusion has similarities with the relationship’s framework based on compatibility context dependent (Shinga et al. 2018).
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The SDGs with more correlations with other SDGs are SDG 4 and SDG 16. They are the most transversal (Blind 2016; Boeren 2019). Education correlates positively with SDG 5, SDG 7, SDG 8, SDG 12, SDG 16 and SDG 17 and negatively with SDG 10. SDG 16 is positively correlated with SDG 4, SDG 5, SDG 7, SDG 8 and SDG 16 and negatively with SDG 3 and SDG 13. In other words, better data from justice and peace indicators show worse indicators of health and climate change.
4 Conclusion
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This case study for Spanish cities takes the municipality as its reference unit, being the municipality the administrative and political entity mainly responsible for a large number of public policies that affect the territory under its jurisdiction.
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There is no single variable, composite indicator or set of indicators that measures sustainability universally (Wilson and Wu 2017). Therefore, the results presented should be interpreted as methodological assumptions and adopted conventions suitable in the Spanish context.
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Data are indicators that point to a situation and do not reflect the urban complexity by themselves. They are limited and can mask part of the everyday reality of cities. Indicators are a tool that provides information showing reality through evidence. Thus, an interpretation exercise is needed. There are as many systems of indicators as realities to be built.
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In view of all these factors, interesting results have been found in the comparison between territories. A large concentration of the tourism sector and a poorer development of education have been identified in the worst-rated areas of the index. In contrast, the municipalities with the highest values of Sustainable Development suffer from population exodus. It is important to note that correlation does not imply causation, and future lines of research should focus on locating the cause-and-effect relationship of the phenomena found.
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On the other hand, the analysis shows that several factors have been identified that relate to the Sustainable Development situation of the various Spanish municipalities included in the sample. In particular, the results show how the municipalities with the best situation show significant positive correlations with the median age of the population, the average annual income per capita and the employment rate of working population between the ages of 20 and 64. By contrast, municipalities with the lowest unemployment rate are the ones with the best results.
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This should ultimately lead us to consider the necessary complicity between active employment policies and sustainability and compliance with the 2030 Agenda, which is a major challenge for public administrations. SDG 8, Decent Work and Economic Growth, shows very low values in several of the Spanish municipalities; however, those with a higher economic activity are the ones that have shown the greatest progress in sustainable development. It is important that Spain is implementing policies aimed at ending job precariousness and promoting the growth and economic development of the regions. Understanding this necessary diligence means promoting educational development, which generates direct social benefits in the productivity of regions and creates decent jobs.
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Using an open data-based approach for planning and implementation will enable a systematic assessment of the annual progress in sustainable development, improving the quality of comparable data on an urban scale and collecting it.
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Focusing on inequalities within certain groups to facilitate their approach. This study has shown acute inequalities in virtually every major city that makes up the sample analyzed. Implementing long-term policies and programs aimed at addressing inequalities between social groups in cities are critical for leveling the playing field and ensuring that all citizens, regardless of where they live, have equal opportunities in life.
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Promoting the exchange of knowledge and mutual learning between cities will be a crucial catalyst for change. Cities can use existing forums to share their experiences and forge new alliances based on shared challenges.
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Collaborations should be encouraged since the scale of the sustainable development challenges is enormous and the resources at the local level are limited. Local governments could rely on non-governmental actors such as universities, civil society and organizations to obtain technical support, collect data, design programs and strategies and support their implementation. As new strategies are defined, other actors, such as the private sector, can also be incorporated to help in supporting the implementation.
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Supporting the central government in its commitment to implement the 2030 Agenda, the Paris Declaration and Accra Agenda for Action and the Spanish Urban Agenda. This can be done by demonstrating local support for sustainable development through campaigns and public funding of the SDGs and, also, by laying the foundations for practical and replicable strategies aimed at achieving the SDG in the cities and the rest of the country.