Efficiency evaluation of sustainable development in BRICS and G7 countries: a Data Envelopment Analysis approach

Camioto, Flávia de Castro; Pulita, Alícia Cristina

doi:10.1590/1806-9649-2022v29e022

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ORIGINAL ARTICLE • Gest. Prod. 29 • 2022 • https://doi.org/10.1590/1806-9649-2022v29e022 copy

Efficiency evaluation of sustainable development in BRICS and G7 countries: a Data Envelopment Analysis approach

Análise do desenvolvimento sustentável nos BRICS e G7: uma abordagem com a Análise Envoltória de Dados

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

In order to measure the impact of the economic growth over the years, the sustainable development concept works to balance three pillars of sustainability - economic, social and environmental. This paper has the objective to compare emerging countries (BRICS) with the most developed countries (G7) by analysing sustainable development. Data Envelopment Analysis (DEA) was used, thorugh the variant SBM (Slacks Based Measured) model. The inputs were CO₂ emission, percentage of unemployed and energy utilization. GDP and life expectancy at birth were used as outputs. The main result was a global average efficency ranking, having the emerging countries in top positions (India, China and Brazil, respectively). In addition, emerging countries have always stood out in the average of the slacks of each analyzed variable. These results are important in terms of being useful for public policies related to sustainable development, especially: (1) to contribute to the discussions related to evaluating the countries, helping to identify those with the best practices with regard to environmental, social and economic aspects in each group; and (2) to guide policy decisions regarding government incentives to promote the development of efficient countries in terms of economic growth and welfare social without harming the environment.

Keywords:
Sustainable development; DEA; Indicator; BRICS; G7

Pillars of sustainability	Definitions	References
Economic	There must be integration between economy and environment in all sectors, such as industry, government and domestic environment to be sustainable.	MacNeill et al. (1991)MacNeill, J., Winsemius, P., & Yakushiji, T. (1991). Beyond Interdependence: the meshing of the world’s economy and the earth’s ecology. New York: Oxford University Press.
	It considers issues related to economic efficiency, short-, medium- and long-term profitability in sectors, avoiding imbalances that may affect agricultural and industrial production.	Cristu et al. (2016)Cristu, C., Angheluţă, S., & Cristu, M. (2016). An overview of sustainable development indicators. The USV Annals of Economics and Public Administration, 16(2), 60-70.
	It considers the efficient use of resources to increase operating profit and maximize market value. It also focuses on the substitution of natural resources, human resources, reuse and recycling.	Olawumi & Chan (2018)Olawumi, T. O., & Chan, D. W. M. (2018). A scientometric review of global research on sustainability and sustainable development. Journal of Cleaner Production, 183, 231-250.
Social	It evaluates the well-being of the population, the human condition and the means to improve the quality of life.	Bellen (2002)Bellen, H. M. V. (2002). Indicadores de sustentabilidade: uma análise comparativa (Tese de doutorado). Universidade Federal de Santa Catarina, Florianópolis.
	It concerns the well-being of all members of a community, equity and social justice, inclusion, cohesion and social solidarity, health and education.	Cristu et al. (2016)Cristu, C., Angheluţă, S., & Cristu, M. (2016). An overview of sustainable development indicators. The USV Annals of Economics and Public Administration, 16(2), 60-70.
	It considers the social well-being of the population, balancing the need of an individual with the need of the group (equity), in addition to public awareness and cohesion, participation and use of local companies and workers.	Olawumi & Chan (2018)Olawumi, T. O., & Chan, D. W. M. (2018). A scientometric review of global research on sustainability and sustainable development. Journal of Cleaner Production, 183, 231-250.
Environmental	The impacts caused in nature by the human can be very harmful to the environment. The environmental pillar aims to maintain a stable base of natural resources and biodiversity.	Cristu et al. (2016)Cristu, C., Angheluţă, S., & Cristu, M. (2016). An overview of sustainable development indicators. The USV Annals of Economics and Public Administration, 16(2), 60-70.
Environmental	It is concerned with limiting human activity to the capacity of existing ecosystems in the locality and also puts emphasis on the quality of human life (air quality, human health).	Olawumi & Chan (2018)Olawumi, T. O., & Chan, D. W. M. (2018). A scientometric review of global research on sustainability and sustainable development. Journal of Cleaner Production, 183, 231-250.

CATEGORY	SUSTAINABLE DIMENSION	VARIABLES
INPUT	Environmental	CO₂ emission
	Environmental	Energy use
	Social	Percentage of unemployed
OUTPUT	Economic	PIB
OUTPUT	Social	Expectativa de vida

Variable	Meaning	Studies that use the variable
CO₂ emission	It comes from the burning of fossil fuels and the manufacture of cement. It includes carbon dioxide produced during the consumption of solid, liquid and gaseous fuels and gas burning	Abreu et al. (2018)Abreu, J., Braga, V., & Correia, A. (2018). Policies and economies impact’s on CO2 emissions in the World. Innovation, Engineering and Entrepreneurship, 505, 771-778.; Balados-Naves et al. (2018)Balados-Naves, R., Banõs-Pino, J. F., & Mayor, M. (2018). Do countries influence neighbouring pollution? A spatial analysis of the EKC for CO2 emissions. Energy Policy, 123, 266-279.; Mardani et al. (2019)Mardani, A., Streimikiene, D., Cavallaro, F., Loganathan, N., & Khoshnoudi, M. (2019). Carbon dioxide (CO2) emissions and economic growth: a systematic review of two decades of research from 1995 to 2017. The Science of the Total Environment, 649, 31-49. PMid:30170214.; Sarkodie & Strezov (2019)Sarkodie, S. A., & Strezov, V. (2019). Effect of foreign direct investments, economic development and energy consumption on greenhouse gas emissions in developing countries. The Science of the Total Environment, 646, 862-871. PMid:30064112.; Gonzalez-Garcia et al. (2018)Gonzalez-Garcia, S., Manteiga, R., Moreira, M. T., & Feijoo, G. (2018). Assessing the sustainabilty of Spanish cities considering environmental and sócio-economic indicators. Journal of Cleaner Production, 178, 599-610. http://dx.doi.org/10.1016/j.jclepro.2018.01.056. http://dx.doi.org/10.1016/j.jclepro.2018... ; Lima et al. (2017)Lima, F., Nunes, M. L., & Cunha, J. (2017). Energy indicators framework and climate change policy implications. In 14th International Conference on the European Energy Market. EEM.; Andrich et al. (2013)Andrich, M. A., Imberger, J., & Oxburgh, E. R. (2013). Inequality as an obstacle to sustainable electricity and transport energy use. Energy for Sustainable Development, 17, 315-325.
Energy use	Refers to the use of primary energy prior to conversion to other end-use fuels	Sarkodie & Strezov (2019)Sarkodie, S. A., & Strezov, V. (2019). Effect of foreign direct investments, economic development and energy consumption on greenhouse gas emissions in developing countries. The Science of the Total Environment, 646, 862-871. PMid:30064112.; Ayoo (2016)Ayoo, C. (2016). The role of efficiency in energy policy. International Journal of Environment and Sustainable Development, 15(4), 423-449.; Andrich et al. (2013)Andrich, M. A., Imberger, J., & Oxburgh, E. R. (2013). Inequality as an obstacle to sustainable electricity and transport energy use. Energy for Sustainable Development, 17, 315-325.
GDP	GDP at purchaser prices is the sum of the gross value added of all resident producers in the economy plus any taxes on products and less any subsidies not included in the value of the products	Mardani et al. (2019)Mardani, A., Streimikiene, D., Cavallaro, F., Loganathan, N., & Khoshnoudi, M. (2019). Carbon dioxide (CO2) emissions and economic growth: a systematic review of two decades of research from 1995 to 2017. The Science of the Total Environment, 649, 31-49. PMid:30170214.; Sarkodie & Strezov (2019)Sarkodie, S. A., & Strezov, V. (2019). Effect of foreign direct investments, economic development and energy consumption on greenhouse gas emissions in developing countries. The Science of the Total Environment, 646, 862-871. PMid:30064112.; Juknys et al. (2018)Juknys, R., Liobikienè, G., & Dagiliute, R. (2018). Deceleration of economic growth: the main course seeking sustainability in developed countries. Journal of Cleaner Production, 192, 1-8.; Gorobets (2011)Gorobets, A. (2011). Corrections to the human development index and alternative indicators of sustainability. International Journal of Sustainable Society, 3(2), 107. http://dx.doi.org/10.1504/IJSSOC.2011.039916 http://dx.doi.org/10.1504/IJSSOC.2011.03... ; Duro & Padilla (2010)Duro, J. A., & Padilla, E. (2010). Inequality acroos countries in energy intensities: an analysis of the role of energy transformation and final energy consumption. Energy Economics, 33, 474-479.
Life expectancy at birth	Indicates the number of years a newborn would live if the prevalent patterns of birth-time mortality were the same throughout their lifetime	Zhang (2013)Zhang, A. (2013). A model of climate change and public health. In World Environmental and Water Resources Congress 2013. Reston: ASCE.; Gorobets (2011)Gorobets, A. (2011). Corrections to the human development index and alternative indicators of sustainability. International Journal of Sustainable Society, 3(2), 107. http://dx.doi.org/10.1504/IJSSOC.2011.039916 http://dx.doi.org/10.1504/IJSSOC.2011.03... ; Knight (2014)Knight, K. W. (2014). Temporal variation in the relationship between environmental demands and well-being: a panel analysis of developed and less-developed countries. Population and Environment, 36, 32-47.
Percentage of unemployed	Refers to the portion of the workforce that is out of work, but available to look for work	González-Mejía et al. (2014)González-Mejía, A. M., Eason, T. N., Cabezas, H., & Suidan, M. T. (2014). Social and economic sustainability of urban systems: comparative analysis of metropolitan statistical areas in Ohio, USA. Sustainability Science, 9(2), 217-228. http://dx.doi.org/10.1007/s11625-013-0227-3. http://dx.doi.org/10.1007/s11625-013-022... ; Gonzalez-Garcia et al. (2018)Gonzalez-Garcia, S., Manteiga, R., Moreira, M. T., & Feijoo, G. (2018). Assessing the sustainabilty of Spanish cities considering environmental and sócio-economic indicators. Journal of Cleaner Production, 178, 599-610. http://dx.doi.org/10.1016/j.jclepro.2018.01.056. http://dx.doi.org/10.1016/j.jclepro.2018...

	Percentage of unemployed	CO₂ emission	Energy use	Life expectancy at birth	GDP
Percentage of unemployed	1
CO₂ emission	-0.3114*	1
Energy use	-0.0672	0.0297	1
Life expectancy at birth	-0.5965*	-0.0030	0.3717*	1
GDP	-0.2807*	0.6611*	0.4186*	0.3178*	1

VARIABLES	GDP	Life expectancy at birth
Percentage of unemployed	-0.515***	-0.028***
Percentage of unemployed	(0.084)	(0.009)
CO₂ emissions	0.382***	-0.005
CO₂ emissions	(0.078)	(0.009)
Energy use	0.529***	0.061***
Energy use	(0.076)	(0.007)
Constant	19.916***	3.9897
Constant	(1.434)	(0.130)
Observations	120	120
Number of num	12	12

Ranking	Country	1	2	3	4	5	Average	Standard deviation
1	India	97.97%	97.86%	97.86%	97.93%	99.45%	98.22%	4.13%
2	China	99.24%	99.73%	98.63%	98.37%	94.47%	98.09%	3.17%
3	Brazil	97.53%	96.42%	97.78%	97.78%	99.02%	97.71%	3.39%
4	Japan	97.19%	98.33%	97.23%	97.26%	96.03%	97.21%	4.11%
5	Italy	93.83%	96.42%	98.94%	98.13%	90.56%	95.58%	6.82%
6	France	92.19%	93.34%	95.44%	96.66%	92.87%	94.10%	6.13%
7	EUA	97.11%	96.65%	92.93%	90.36%	85.13%	92.43%	8.19%
8	United Kingdom	93.98%	93.03%	93.88%	94.25%	82.61%	91.55%	7.72%
9	Germany	74.74%	75.97%	80.50%	85.05%	84.04%	80.06%	8.84%
10	Canada	46.72%	50.25%	45.54%	52.33%	48.40%	48.65%	5.63%
11	Russia	25.90%	25.88%	28.18%	30.20%	31.43%	28.32%	5.58%
12	South Africa	13.24%	12.29%	12.93%	13.35%	13.75%	13.11%	1.74%

Ranking	Country	Classic Frontier	Inverted Frontier	Composite Index normalized
1	India	98.22%	16.12%	100.00%
2	Brazil	97.71%	17.00%	99.24%
3	France	94.10%	15.67%	97.98%
4	Italy	95.58%	17.36%	97.87%
5	Japan	97.21%	24.13%	95.04%
6	United Kingdom	91.55%	18.57%	94.99%
7	Germany	80.06%	26.08%	84.56%
8	China	98.09%	97.87%	55.03%
9	EUA	92.43%	92.66%	54.79%
10	Canada	48.65%	87.53%	33.56%
11	Russia	28.32%	71.05%	31.45%
12	South Africa	13.11%	98.68%	7.93%

	Alpha - α (weight of each criterion)
Countries	0.1	0.2	0.3	0.4	0.5	0.6	0.7	0.8	0.9	1
India	100.00%	100.00%	100.00%	100.00%	100.00%	100.00%	100.00%	100.00%	100.00%	100.00%
Brazil	99.01%	99.07%	99.13%	99.18%	99.24%	99.29%	99.34%	99.39%	99.43%	99.48%
France	99.98%	99.46%	98.95%	98.46%	97.98%	97.52%	97.07%	96.64%	96.21%	95.81%
Italy	98.38%	98.24%	98.11%	97.99%	97.87%	97.75%	97.63%	97.52%	97.42%	97.31%
Japan	91.42%	92.37%	93.29%	94.18%	95.04%	95.88%	96.69%	97.47%	98.23%	98.97%
United Kingdom	96.63%	96.20%	95.78%	95.38%	94.99%	94.61%	94.24%	93.89%	93.54%	93.21%
Germany	87.37%	86.63%	85.92%	85.23%	84.56%	83.91%	83.28%	82.68%	82.08%	81.51%
China	13.74%	24.58%	35.06%	45.21%	55.03%	64.56%	73.79%	82.74%	91.43%	99.87%
EUA	18.58%	28.08%	37.27%	46.17%	54.79%	63.14%	71.24%	79.09%	86.71%	94.11%
Canada	18.85%	22.71%	26.45%	30.06%	33.56%	36.95%	40.24%	43.43%	46.53%	49.53%
Russia	33.86%	33.23%	32.62%	32.03%	31.45%	30.90%	30.36%	29.83%	29.33%	28.83%
South Africa	2.93%	4.24%	5.51%	6.74%	7.93%	9.08%	10.19%	11.28%	12.33%	13.35%

Country	Percentage of unemployed	CO₂ emission	Energy use	Life expectancy	GDP
South Africa	66.80%	6.89%	50.10%	33.46%	677.19%
Brazil	1.28%	0.01%	0.45%	0.17%	3.52%
China	0.20%	4.72%	0.03%	0.00%	0.55%
India	1.09%	0.69%	0.00%	0.04%	2.65%
Russia	31.45%	28.45%	24.79%	20.71%	307.25%
Germany	22.20%	0.91%	18.04%	0.59%	15.97%
Canada	10.56%	1.04%	54.01%	0.06%	119.75%
EUA	12.47%	5.69%	3.88%	0.52%	0.00%
France	5.86%	0.11%	2.61%	0.12%	6.85%
Italy	1.81%	0.00%	0.00%	0.00%	8.94%
Japan	2.51%	0.27%	2.26%	0.05%	2.38%
United Kingdom	5.32%	1.70%	1.97%	0.15%	12.52%

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[1] This table represents the correlation matrix between the model variables. Statistically significant coefficients: (*) 5% level.