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Sustainable Development Goals Indicators at Territorial Level: Conceptual and Methodological Issues—The Italian Perspective

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Abstract

The 2030 Agenda for Sustainable Development (2015) can be considered the synthesis of a debate, which sets the sustainable development as a priority for the International Community. The achievement of the sustainable development goals has made necessary to develop a system of indicators. Indicators and data should be collected and reported sub-nationally, giving attention to the territory. This is a necessity even more for Italy, a country historically characterized by strong regional specificities and differences, which find their radicalization in the so-called North–South gap. In this paper, we want to examine and monitor the Italian situation as to the achievement of the SDGs, based on the analysis of the Regions, to highlight potential differences or territorial homogeneity. In particular, we want to emphasize not only how there is actually a gap between the North and the South of the country, but also how the synthesis tends often to be representative of situations profoundly different from each other, as a result of different values in the basic indicators, or similar situations between them. Due to the difficulty of reporting on a paper a detailed analysis of all 17 sustainable development goals, we focus only on the first three goals one. In particular, for each goal we select indicators all useful for the analysis of regional realities and appropriate some for monitoring the present condition, others for providing information on the future one (risk). The research methodology is to use the Adjusted Mazziotta–Pareto Index for creating a composite index for each goal considered. This analysis is preceded by an exploratory analysis of the basic indicators over time through the use of within and between correlations and the average PCA.

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Notes

  1. For a review, please see: Gibson (2010), Elliott (2013) and Grober (2016).

  2. For a complete analysis of the ecological paradigm on sustainable development, please see Elliott (2013).

  3. The Millennium Summit of the United Nations in 2000 established the MDGs, these eight international development goals for the year 2015:

    1. 1.

      To eradicate extreme poverty and hunger.

    2. 2.

      To achieve universal primary education.

    3. 3.

      To promote gender equality and empower women.

    4. 4.

      To reduce child mortality.

    5. 5.

      To improve maternal health.

    6. 6.

      To combat HIV/AIDS, malaria, and other diseases.

    7. 7.

      To ensure environmental sustainability.

    8. 8.

      To develop a global partnership for development.

  4. Some authors point out that even at the time of national unification Italy was characterized by evident inequalities and backwardness of the South compared to the rest of the country and how this situation has influenced the future development. Other authors, on the contrary, reduce the importance and role of the initial gap between the different areas in future development. For a review, please see Lepore (2012).

  5. Regions have legislative power, except for the determination of fundamental principles, reserved to the State.

  6. Within the composite indicator framework, methods for weighting indicators can be broadly categorized into three main groups: equal weighting, statistic-based weighting, public/expert opinion-based weighting (Gan et al. 2017, 492).

  7. For example, in the case of goal 3, if we intended to construct a composite whose increase coincides with an improvement in health, the life expectancy would have positive polarity, while the smoking rate would be negative. If, on the contrary, we wanted to construct a composite whose increase indicates a worsening of health (for instance, a risk indicator), the life expectancy would have negative polarity, while the smoking rate would be positive.

  8. It is possible to observe (also in this work) how in reality the composite often has values outside this range. What might seem a limit of AMPI, on the contrary, is one of its qualities, as it allows highlighting the presence of a strong variability in the time series of the basic indicators.

  9. For more information, please see: Rutherford (2011).

  10. Rmcorr is an atypical application of ANCOVA, with an opposite purpose. The analysis of covariance is a statistical method used to test the effects of categorical variables on a continuous dependent variable, controlling for the effects of selected other continuous nuisance variables, which co-vary with the dependent. On the contrary, we can use “rmcorr to determine the relationship between two continuous variables, while controlling for the effect of the categorical variable, which in this case is the between-participants variance” (Bakdash and Marusich 2017, 3).

  11. This method is equivalent to fitting parallel lines through the data of each observation and the residual sum of squares represents the variation about these lines.

  12. The rmcorr generally has much greater statistical power than a standard Pearson correlation using averaged data, and its power increases exponentially when either the value of the number of repeated observations, or that of the total number of unique observations, increases.

  13. These approaches may lead to misleading conclusions, because they do not offer an explicit description of the three-way interaction in the data. For this reason, some specific techniques have been developed to obtain direct solutions for three-way dataset (for a review, please see: Kroonenberg 1983; Kiers and Mechelen 2001; Kroonenberg 2008). The strength of three-way methods is that they summarize the entities of each mode through a few components and describe the relations between these components (Kiers and Mechelen 2001, 84). For the objectives of exploratory analysis in the construction of composites, these techniques would probably be too sophisticated and would still require more specific and broader treatment.

  14. We would have been possible to include the indicator of adequate nutrition among the risk factors. As is evident, it can be considered both in the current condition and in the risk. However, we decided not to include it as a risk factor for Goal 2, especially because we did not have other risk indicators available. Considering it as the only risk factor would probably be limiting for the concept.

  15. We must point out that healthy life expectancy is constructed using the prevalence of individuals who respond positively ("well" or "very well") to the perceived health question. The indicator includes in itself part of the good health index. Therefore, the high values of the CB and CW are also due to the way in which the indicator in question was constructed.

  16. The trends are fluctuating for both indicators considered.

  17. The decrease concerns all three indicators: the life expectancy at birth passes from 82.8 to 82.7; the healthy life expectancy at birth from 58.8 to 58.7 and the life expectancy without activity limitations at 65 years goes from 9.8 to 9.7. These decreases are very slight. However, we must consider that life expectancies vary very slowly over time and, therefore, could have a very strong weight, especially when compared to a positive trend in previous years.

  18. Other behaviours may affect health; however, we cannot include them in our analysis because of lack of data.

  19. All individuals who practice at least one of the behaviours at risk are identified as "consumers at risk", exceeding the daily consumption of alcohol (according to specific thresholds for sex and age) or concentrating in a single occasion of consumption the assumption of more than 6 alcoholic units of any drink (binge drinking).

  20. The indicator has a decreasing trend until 2015. In 2016, it pick-ups, followed in 2017 by a slight decrease.

  21. Looking at the average values for simplicity, 25.5% of regional population present at least one behaviour at risk in the consumption of alcohol compared to 17.7% of the national population.

  22. The trend of the adequate nutrition index in 2017 is the highest amongst all the regional ones (23.6%).

References

  • Aguirre-Urreta, M. I., Rönkkö, M., & Marakas, G. M. (2016). Omission of causal indicators: Consequences and implications for measurement. Measurement: Interdisciplinary Research and Perspectives, 14(3), 75–97.

    Google Scholar 

  • Aki, T., & Akihisa, M. (2007). Sustainable development in Thailand: Lessons from implementing local agenda 21 in three cities. The Journal of Environment & Development, 16, 269–289.

    Article  Google Scholar 

  • Alaimo, L. S. (2019). Sustainable development and territorial differences: An Italian analysis of economic sustainability. Working papers of the PhD Course in Applied Social Sciences, Department of Social Sciences and Economics, Sapienza University of Rome. Paper n. 1/2019. https://web.uniroma1.it/disse/sites/default/files/DiSSE_Alaimo%20wp1_2019.pdf.

  • Bagozzi, R. P. (2007). On the meaning of formative measurement and how it differs from reflective measurement: Comment on Howell, Breivik and Wilcox (2007). Psychological Methods, 12(2), 229–237.

    Article  Google Scholar 

  • Bakdash, J. Z., & Marusich, L. R. (2017). Repeated measures correlation. Frontiers in Psychology, 8, 1–13. https://doi.org/10.3389/fpsyg.2017.00456.

    Article  Google Scholar 

  • Becker, W., Saisana, M., Paruolo, P., & Vandecasteele, I. (2017). Weights and importance in composite indicators: Closing the gap. Ecological Indicators, 80, 12–22.

    Article  Google Scholar 

  • Bland, J. M., & Altman, D. G. (1995a). Calculating correlation coefficients with repeated observations: Part 1. Correlation within subjects. BMJ, 310, 446. https://doi.org/10.1136/bmj.310.6977.446.

    Article  Google Scholar 

  • Bland, J. M., & Altman, D. G. (1995b). Calculating correlation coefficients with repeated observations: Part 1. Correlation between subjects. BMJ, 310, 633. https://doi.org/10.1136/bmj.310.6980.633.

    Article  Google Scholar 

  • Blewitt, J. (2015). Understanding sustainable development. London: Routledge.

    Google Scholar 

  • Böhringer, C., & Jochem, P. E. P. (2007). Measuring the immeasurable: A survey of sustainability indices. Ecological Economics, 63, 1–8.

    Article  Google Scholar 

  • Bollen, K. A. (2007). Interpretational confounding is due to misspecification, not to type of indicator: Comment on Howell, Breivik and Wilcox (2007). Psychological Methods, 12(2), 219–228.

    Article  Google Scholar 

  • Bollen, K. A., & Diamantopoulos, A. (2017). In defense of causal-formative indicators: A minority report. Psychological Methods, 22(3), 581–596.

    Article  Google Scholar 

  • Bond, A. J., & Morrison-Saunders, A. (2009). Sustainability appraisal: Jack of all trades, master of none? Impact Assessment and Project Appraisal, 27(4), 321–329.

    Article  Google Scholar 

  • Bruyninckx, H., Happaerts, S., & van den Brande, K. (2012). Sustainable development and subnational Governments policy-making and multi-level interactions. Basingstoke: Palgrave Macmillan.

    Book  Google Scholar 

  • Dalal-Clayton, B., & Sadler, B. (2005). Strategic environmental assessment. A sourcebook and reference guide to international experience. London: Earthscan.

    Google Scholar 

  • Devuyst, D. (2000). Linking impact assessment and sustainable development at the local level: The introduction of sustainability assessment systems. Sustainable Development, 8, 67–78.

    Article  Google Scholar 

  • Diamantopoulos, A., Riefler, P., & Roth, K. P. (2008). Advancing formative measurement models. Journal of Business Research, 61(12), 1203–1218.

    Article  Google Scholar 

  • Diamantopoulos, A., & Siguaw, J. A. (2006). Formative versus reflective indicators in organizational measure development: A comparison and empirical illustration. British Journal of Management, 17(4), 263–282.

    Article  Google Scholar 

  • Edwards, J. R. (2011). The fallacy of formative measurement. Organizational Research Methods, 14(2), 370–388.

    Article  Google Scholar 

  • Elliott, J. A. (2013). An introduction to sustainable development. London: Routledge.

    Google Scholar 

  • Endress, L. H. (2015). Scarcity, security and sustainable development. In U. Chakravorty, A. Balisacan, & M.-L. Ravago (Eds.), Sustainable economic development: Resources, environment, and institutions (pp. 49–66). San Diego: Academic Press.

    Chapter  Google Scholar 

  • Engel, J. R. (1990). Introduction: The ethics of sustainable development. In J. R. Engel & J. G. Engel (Eds.), Ethics of environment and development: Global challenge, International response (pp. 10–11). Tucson: University of Arizona Press.

    Google Scholar 

  • Gan, X., Fernandez, I. C., Guo, J., Wilson, M., & Zhao, Y. (2017). When to use what: Methods for weighting and aggregating sustainability. Ecological Indicators, 81, 491–502.

    Article  Google Scholar 

  • Gibson, R. B. (2010). Sustainability assessment: Criteria and processes. London: Earthscan.

    Google Scholar 

  • Grober, U. (2016). The discovery of sustainability. The genealogy of a term. In J. C. Enders & M. Remig (Eds.), Theories of sustainable development (pp. 6–15). London: Routledge.

    Google Scholar 

  • Guillén-Royo, M. (2016). Sustainability and wellbeing: Human-scale development in practice. London: Routledge.

    Google Scholar 

  • Hartmuth, G., Huber, K., & Rink, D. (2008). Operationalization and contextualization of sustainability at the local level. Sustainable Development, 16, 261–270.

    Article  Google Scholar 

  • Hatakeyama, T. (2018). Sustainable development indicators: Conceptual frameworks of comparative indicators sets for local administrations in Japan. Sustainable Development, 26, 683–690.

    Article  Google Scholar 

  • Herva, M., Franco, A., Carraso, E. F., & Roca, E. (2011). Review of corporate environmental indicators. Journal of Cleaner Production, 19, 1687–1699.

    Article  Google Scholar 

  • Howell, R. D., Breivik, E., & Wilcox, J. B. (2007). Reconsidering formative measurement. Psychological Methods, 12(2), 205–218.

    Article  Google Scholar 

  • Istat. (2015). Bes 2015: Il benessere equo e sostenibile in Italia. Rome: Italian National Institute of Statistics—Istat.

  • Istat. (2018a). Indicators for the measurement of equitable and sustainable well-being. Downloaded 20/12/2018. https://www.istat.it/en/well-being-and-sustainability/the-measurement-of-well-being/indicators.

  • Istat. (2018b). Indicators for the United Nations sustainable development goals. Downloaded 20/12/2018. https://www.istat.it/en/well-being-and-sustainability/sustainable-development-goals/istat-indicators-for-sustainable-development.

  • Istat. (2018c). Territorial indicators for development policies. Downloaded 20/12/2018. https://www.istat.it/it/archivio/16777.

  • Kanbur, R., Patel, E., & Stiglitz, J. (2016). Sustainable development goals and measurement of economic and social progress. http://policydialogue.org/files/events/Ravi_Kanbur.pdf.

  • Kiers, H. A. L., & Mechelen, I. V. (2001). Three-way component analysis: Principles and illustrative application. Psychological Methods, 6(1), 84–110.

    Article  Google Scholar 

  • Kondyli, J. (2010). Measurement and evaluation of sustainable development. A composite indicator for the islands of the North Aegean region, Greece. Environmental Impact Assessment Review, 30, 347–356.

    Article  Google Scholar 

  • Kroonenberg, P. M. (1983). Three-mode principal component analysis. Theory and applications. Leiden: DSWO Press.

    Google Scholar 

  • Kroonenberg, P. M. (2008). Applied multiway data analysis. Hoboken, NJ: Wiley.

    Book  Google Scholar 

  • Latouche, S., & Macey, D. (2009). Farewell to growth. Cambridge: Polity Press.

    Google Scholar 

  • Lazarsfeld, P. F. (1958). Evidence and inference in social research. Daedalus, 87(4), 99–130.

    Google Scholar 

  • Lepore, A. (2012). Il divario Nord-Sud dalle origini a oggi. Evoluzione storica e profile economici. In M. Pellegrin (Ed.), Elementi di diritto pubblico dell’economia (pp. 347–367). Padova: CEDAM.

    Google Scholar 

  • Maggino, F. (2015a). Subjective well-being and subjective aspects of well-being: Methodology and theory. Rivista Internazionale di Scienze Sociali, 1, 89–121.

    Google Scholar 

  • Maggino, F. (2015b). Assessing the subjective wellbeing of nations. In W. Glatzer, L. Camfield, V. Møller, & M. Rojas (Eds.), Global handbook of quality of life. Exploration of well-being of nations and continents (pp. 803–822). Cham: Springer.

    Chapter  Google Scholar 

  • Maggino, F. (2017). Developing indicators and managing the complexity. In F. Maggino (Ed.), Complexity in society: From indicators construction to their synthesis (pp. 87–114). Cham: Springer.

    Chapter  Google Scholar 

  • Mazziotta, C., Mazziotta, M., Pareto, A., & Vidoli, F. (2010). La sintesi di indicatori territoriali di dotazione infrastrutturale: Metodi di costruzione e procedure di ponderazione a confronto. Review of Economics and Statistics for Regional Studies, 1(1), 7–33.

    Google Scholar 

  • Mazziotta, M., & Pareto, A. (2015). Comparing two non-compensatory composite indices to measure changes over time: A case study. Statistika, 95(2), 44–53.

    Google Scholar 

  • Mazziotta, M., & Pareto, A. (2016). On a generalized non-compensatory composite index for measuring socio-economic phenomena. Social Indicators Research, 127(3), 983–1003.

    Article  Google Scholar 

  • Mazziotta, M., & Pareto, A. (2017). Synthesis of indicators: The composite indicators approach. In F. Maggino (Ed.), Complexity in society: From indicators construction to their synthesis (pp. 161–191). Cham: Springer.

    Google Scholar 

  • Meadows, D. H., Meadows, D. L., Randers, J., & Behrens, W. W., III. (1972). Limits to growth. New York: Universe Books.

    Google Scholar 

  • Moldan, B., & Dahl, A. L. (2012). Challenges to sustainability indicators. In T. Hák, B. Moldan, & A. L. Dahl (Eds.), Sustainability indicators. A scientific assessment (pp. 1–24). Washington, DC: Island Press.

    Google Scholar 

  • Moreno, P. S., Fidelis, T., & Ramos, T. B. (2014). Measuring and comparing local sustainable development through common indicators: Constraints and achievements in practice. Cities, 39, 1–9.

    Article  Google Scholar 

  • Nardo, M., Saisana, M., Saltelli, A., & Tarantola, S. (2005). Tools for composite indicators building. European Commission, EUR 21682 EN. Institute for the Protection and Security of the Citizen, Ispra, Italia. http://publications.jrc.ec.europa.eu/repository/bitstream/JRC31473/EUR%2021682%20EN.pdf.

  • Nurse, K. (2006). Culture as the fourth pillar of sustainable development. Small States: Economic Review and Basic Statistics, 11, 28–40.

    Google Scholar 

  • Parodi, O. (2015). The missing aspect of culture in sustainability concepts. In J. C. Endress & M. Remig (Eds.), Theories of sustainable development (pp. 169–187). London: Routledge.

    Google Scholar 

  • Pawlowski, A. (2008). How many dimensions does sustainable development have? Sustainable Development, 16, 81–90.

    Article  Google Scholar 

  • Prescott-Allen, R. (2001). The well-being of nations: A country-by-country index of quality of life and the environment. Washington, DC: Island Press.

    Google Scholar 

  • Rutherford, A. (2011). ANOVA and ANCOVA. A GLM approach (2nd ed.). Hoboken, NJ: Wiley.

    Book  Google Scholar 

  • Sacconaghi, R. (2017). Building knowledge. Between measure and meaning: A phenomenological approach. In F. Maggino (Ed.), Complexity in society: From indicators construction to their synthesis (pp. 51–68). Cham: Springer.

    Chapter  Google Scholar 

  • Sachs, W. (1999). Planet dialectics. Explorations in environment and development. London: Zen Books.

    Google Scholar 

  • Sachs, J. D. (2015). The age of sustainable development. New York: Columbia University Press.

    Book  Google Scholar 

  • Saisana, M., & Tarantola, S. (2002). State-of-the-art report on current methodologies and practices for composite indicator development. Report EUR 20408 EN. European Commission–Joint Research Centre, Ispra. https://publications.europa.eu/en/publication-detail/-/publication/9253d939-b47b-4428-b792-619e6b6c8645.

  • Seghezzo, L. (2009). The five dimensions of sustainability. Environmental Politics, 18, 539–556.

    Article  Google Scholar 

  • Sen, A. (2000). Development as freedom. New York: Anchor Books.

    Google Scholar 

  • Turner, R. K., Pearce, D., & Bateman, I. (1993). Environmental economics. An elementary introduction. Baltimore: The Johns Hopkins University Press.

    Google Scholar 

  • United Nations Development Programme. (2014). Sustaining human progress: reducing vulnerabilities and building resilience. New York: Human Development Report.

    Book  Google Scholar 

  • United Nations General Assembly, 66th Session. (2012). The future we want. New York: United Nations.

    Google Scholar 

  • Wichaisri, S., & Sopadang, A. (2018). Trends and future directions in sustainable development. Sustainable Development, 26, 1–17.

    Article  Google Scholar 

  • Wilcox, J. B., Howell, R. D., & Breivik, E. (2008). Questions about formative measurement. Journal of Business Research, 61(12), 1219–1228.

    Article  Google Scholar 

  • World Commission on Environment and Development—WCED. (1987). Our common future. Oxford: Oxford University Press.

    Google Scholar 

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  1. Sapienza University of Rome, Rome, Italy

    Leonardo S. Alaimo & Filomena Maggino

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  1. Leonardo S. Alaimo
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Table 1 Basic indicators: ID; description; source; years; polarity
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Alaimo, L.S., Maggino, F. Sustainable Development Goals Indicators at Territorial Level: Conceptual and Methodological Issues—The Italian Perspective. Soc Indic Res 147, 383–419 (2020). https://doi.org/10.1007/s11205-019-02162-4

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