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Social-environmental index: Combining social and biophysical indicators reveals limits to growth

Citation

Rigal, Stanislas (2022), Social-environmental index: Combining social and biophysical indicators reveals limits to growth, Dryad, Dataset, https://doi.org/10.5061/dryad.866t1g1rq

Abstract

The negative impact of the dominant socio-economic paradigm on the biosphere, on the climate, and on societies themselves are acute. Yet, the success of countries is measured by indicators known to be limited because they target a socially attractive but environmentally unsustainable model of society. A myriad of indicators have been proposed to address this lack of relevant measurements that assess the real social achievements of countries. At the same time, the impacts of human societies on life and climate have become increasingly well monitored and have shown the ecological deadlock of the dominant development model. Although social and environmental thresholds have been highlighted, combined indices that allow countries to track their trajectories toward greater social justice without exceeding biophysical thresholds are still lacking. A combined Socio-Environmental Index (SEI) is constructed here to fill this gap. The relationship between SEI and Gross Domestic Product (GDP), population density, and Sustainable Development Index (SDI) is then analyzed. This allows for a re-examination of the Easterlin paradox from a social and environmental perspective. In addition, considering population density allows to test the influence of population on the country's sustainability success. It is shown that combining social and environmental thresholds into a combined index is not only feasible but provides a useful complementary tool to detailed and specific social or environmental indicators. SEI highlights and quantifies the limits, already exceeded in many countries, beyond which economic development is clearly related to a decline in social achievements and a crossing of biophysical thresholds. Unlike GDP, population density and population growth were not found as being related to the current unsustainable development model. Therefore, the results call for degrowth in the environmental impact of high-income countries which may result in social improvements and yield room of maneuver for the development of social foundations in other countries. All of these transformations require new narratives, goals, and measurement tools which can be partly provided by SEI.

Methods

Initial datasets from O’Neill, D. W., Fanning, A. L., Lamb, W. F., & Steinberger, J. K. (2018). A good life for all within planetary boundaries. Nature sustainability, 1(2), 88-95 (data_publi.csv) and site localisation (social_thresholds.csv and planet_boundaries.csv) for 2011 values and see details in README.txt for time-series and socio-economical data (Chapter2OnlineData.csv, Life_expectancy2.csv, FAOSTAT_data_old.csv, FAOSTAT_data.csv, Sanitation2.csv, Poverty2.csv, Access_electricity2.csv, Education2.csv, Unemployment2.csv, cba.txt, country_hanpp.csv, NFA_2019_public_data.csv, tradereport_"year".txt, UNdata_Export_20210427_172302587.csv, UNdata_Export_20200716_162002498.csv, country_size.csv, SDI.csv: sustainable development index time-series).

Final data SEI.csv are produced following R scripts that are available in the Rmarkdown report (Script_SEI.Rmd) with R script explaining how data analyses were conducted (also visible as a .html file).

Usage Notes

Read the README.txt for data details.

All steps to process data from initial datasets to final data are explained in the Rmarkdown file.

Funding