Socioeconomic and Environmental Performance: A Composite Index and Comparative Application to the USA and China

4. Socioeconomic and Environmental Performance of the USA & China

According to Climate Analytics (2014), the USA and China are responsible for between 35% and 45% of the current world emissions of CO2. However, neither of these two countries is in the frontier of techniques to improve their respective patterns of energy efficiency. Of course, their joint effort would help considerably to prevent threatening climate change, if they decide to limit the current use of conventional energy and apply an enhanced effort towards a policy of sustainable development. In both countries there is evidence of concern for finding sustainable ways to produce and consume energy. Despite this concern, however, the results have been insufficient to make a major impact on the continuing undesirable transformations of the environment.

In the last few decades, China has taken a big jump in its rate of economic growth. Nowadays, its GNP is about half of the USA while the average per capita consumption of electricity of USA is four times China’s. In the last 10 years, the annual growth rate of GNP of China was 10.5% compared to USA’s 1.6%. Most of it is produced in these economies by burning fossil fuel. In neither is there an important economic sector leading the world in the effort to substitute these fuels for those which can mitigate the effects on climate change. The energy consumption of the industrial sector in China is increasing significantly and recently the national government took some steps in the direction of the use of sustainable energy, but neither China nor the USA is adopting the more environmentally friendly standards of the European Union in this matter. For an illuminating view on the needed institutions and policies, see Costanza et al (2015), which presents a well-worth outlining on this matter.

This being the case, we agree with Johnson (2011, p. 19) that “Our world is headed into a perfect storm of an interconnected financial, ecological and social crisis. Almost all forward-looking assessments demonstrate that business as usual and incremental improvements will not be sufficient to take us to a future world blessed by equitable prosperity, safety and contentment”. On the other hand, if the USA and China were to set a good example and start an effective program of sustainable development, we should become less pessimistic about the future of the planet we share.

The October issue of “Climate Analytics” (2014) indicates that, if China and the USA were to adopt, together, the most ambitious policies of efficiency used by the European Union, it would be possible by 2030 to reduce the emissions of CO2 to 10% below the current policy projection of “Climate Action Tracker”. This may well be a reasonable justification for why we decided to compare here the socioeconomic and environmental performance of these two countries, taking as a theoretical indicator the composite Index of Welfare presented in the previous section.

The results of the present enquiry are somewhat preliminary. They can be considered more of an illustration. We should also mention that our approach does not take into consideration that the relationship between environmental sustainability and sustainable development is to a large extent a function of long term trajectories, and that our time series of statistical data is not long enough. We contend that such long series is not available. To some extent however, it may be justified to try to draw conclusions from the data available even though they are not a totally satisfactory sample.

As an application of the complete set of variables for USA and China, we will use the four variables already defined. To help the exposition, the variables and their extended definitions are shown in Table 1.

In order to calculate the composite index of Welfare, we use the period 2002 to 2012. It is worth mentioning that the limits (bounding conditions) we use are based to a large extent on the maximum and minimum values of the four variables CO2CAP (ϒ), WATSAN (τ), HDI (ϕ) and SHARENEW (ζ). They are expressed in percentage changes on the four axes, as indicated in table 2. The meaning of the CO2CAP has been already explained above. Here, we consider CO2 only as a proxy for greenhouse gases (effects) which penetrate the atmosphere, absorbing and emitting radiation. Anthropogenic CO2 emissions come from combustion of carbon-based fuels (primarily wood, coal, oil and natural gas). Since the beginning of the industrial revolution, the burning of fossil fuels and extensive devastation of native forests has contributed to a 40% increase in the atmospheric concentration of CO2. The temperature in the planet has gone up 0.8° Celsius since 1880, on average. Furthermore, there is an acceleration of global warming since World War II. This process, if not contained, will drive the planet to a catastrophe.

Name Definition Description Source & Data Link
CO2CAP (ϒ) Per capita dioxide emissions from the consumption of energy Metric tons of carbon dioxide The World Bank Group
WATSAN (τ) Access to drinking water & sanitation Percentage of population with access to improved drinking water & sanitation Yale Center for Environmental Law and Policy (YCELP) and Center for International Earth Science Information Network (CIESIN), Columbia University
Human development index The index combines three major indicators: health, education and living standard. United Nations Development Program (UNDP)
SHARENEW (ζ) Share of renewables in total consumption of energy Electricity from renewable (hydro, wind, geothermal and solar) plus biomass consumption all divided by the total energy consumption. Global statistical energy yearbook 2014

Source: The authors’ own elaboration from a number of reports

Concerning WATSAN (τ), its welfare implications are quite obvious. To gain access to improved drinking water and sanitation is a vital step towards improving health and well-being. Despite the progress worldwide, the planet remains off-track concerning both targets, for safe water and for sanitation. The economic gains from provision of improved services of drinking water and sanitation must comply with international standards. The adoption of the Millennium Development Goals demonstrated the inadequacies of provision of these services which were carefully examined in the document. They are important with respect to their ecol­ogical, economic and social functions, and also provide important benefits to the ecosystem.

There is no need to emphasize here the importance of the Human Development Index (HDI). However, we should take into consideration that in the 2010 Report a further Inequality-adjusted Human Development Index (IHDI) was introduced. Income distribution and concentration are important indicators of the real wealth of nations. The well documented book by Thomas Piketty (2014) shows that inequality is currently rising in developed countries. He also comments extensively on its harmful effects. In the present article the simple HDI is used. We still do not have a long enough statistical series for an examination of the relevant impact of socioeconomic policies for changing the income distribution on the pathways to human development. For reference, see the United Nations Development Programme’s Human Development Report, released in July 2014.

We explain now the SHARENEW indicator. Energy is a vital element in human life and to secure a sufficient and accessible supply is crucial for sustainability in contemporary societies. The demand for energy is increasing rapidly and the trend is likely to continue. Renewable energy—solar, wind, geothermal, modern biomass and hydroelectric—requires appropriate policies and new technologies. Fossil fuels in their crude form, such as wood, coal and oil, have traditionally been used as energy resources extensively. Society has been acknowledging that, although they dominate the market, they present high levels of pollutants, and that a significant effort must be made to reduce their presence in the structure of the planet’s economies. This is the reason why we introduce the variable, demand for renewable energy divided by the total expenditures on energy.

Table 2: Environmental Variables—Calculated Data

Environmental Variables (% change)
China USA
2002-2003 2011-2012 2002-2003 2011-2012
11,56 8,90 0,07 -6,93
6,19 0,00 0,15 0,00
1,34 4,08 0,53 0,22
-12,21 1,58 6,20 1,05

Source: The authors’ own elaboration from information in Table 1

Now that the four indicators are described above, it is time to deal with the calculation of the composite index. Naturally, the usefulness of the ideal bounding (wonderland) configuration requires the establishment of suitable numerical values for the four variables. Then, we need to establish the two limits, “awful” and “desirable”, for each. Here we introduce statistical data for China and the USA. We estimate the average values for the years 2002/2003 and 2011/2012 in order to compare the changes in the two countries which occurred over the interval of ten years. Such averages of the two years, for the initial and terminal periods, tend to reduce the weight of any peculiarities of an atypical year. The results are shown in Table 2.

Table 3 shows the calculated superior (sup) and inferior (inf) limits given by expressions (1) and (2) as well as the Desirableland configuration. The perceptions and dimensions of global climate change may, in the long run, prove to be the most significant task in terms of both its potential damages and its cost. We will restrict the discussion to what we view as being the most salient points. Unfortunately, the empirical evidence to date has not provided overwhelming support for any configuration of the Wonderland parameters. However, from historical circumstances, we are able to represent a kind of normative limits, the bounding conditions as explained previously.

To proceed, consider first CO2CAP. We want to encounter the extreme points (awful and desirable) of the interval corresponding to that variable. In order to determine the lower limit (awful), we just take the average between the observed lower limits on both countries. Notice that this average is taken under the assumption that the worst performance between the two countries gets weight equal to 2/3 and the best one equal to 1/3. We determine the upper limit (desirable) in a similar fashion, but we inverse the weights. In other words, we consider 2/3 for the best and 1/3 for the other. Observe that these weights were obtained through the method of “convergence of opinions in group”—graph algorithm.§ Such weights indicate that the former has a superior performance and the latter, an inferior one. We consider the upper limit (desirable) in a similar fashion. We proceed likewise for the remaining three variables.

Table 3: Bounding Conditions and Desirableland

Bounding Conditions
China USA Desirableland
11,56 ≥ ϒ ≥ 8,90 0,07 ≥ ϒ ≥ -6,93 7,72 ≥ϒ ≥-2,02
0,00 ≤ τ ≤ 6,19 0,00 ≤ τ ≤ 0,15 0,00 ≤ τ≤ 4,17
1,34 ≤ ϕ ≤ 4,08 0,22 ≤ ϕ ≤ 0,53 0,96 ≤ ϕ ≤ 2,90
-12,21≤ ζ ≤ 1,58 1,05 ≤ ζ ≤ 6,20 -7,79 ≤ ζ ≤ 4,65

Source: The authors’ own elaboration from information in Table 2.

Thus, according to expression (2):

ϒsup – ϒinf = -9,74 τsup – τinf = 4,17 ϕ sup – ϕ inf = 1,94 ζsup – ζinf = 12,44 (7)

Since the numerical value of b has been already defined (square root of 2 divided by 2), we will substitute this value in expression (4). This leads us to the transformations required to obtain the corresponding numerical values of the four original variables given by the Greek symbols. That is, the primed ones given by the set of expressions (7). As an example, we will take the transformations of ϒ and then ϕ.


ϒ’ = (b (ϒ – ϒ inf))/Γ

ϒ’ = (√1/2 (ϒ – 7,72))/-9,74 = (√1/2 (7,72- ϒ ))/9,74                (8)

HDI ϕ:

ϕ’ = b (ϕ – ϕ inf)/Φ

ϕ’ = √1/2 (ϕ – 0,96)/1,94                                                            (9)

In the same way, we can find the scale transformations of the other two variables:

τ’ = √1/2 τ /4,17                                                                       (10)

ζ’ = √1/2 (ζ + 7,79) / 12,44                                                       (11)

Substituting the values of Table 3 in the equations (8) to (11), we obtain the following results:

Table 4: Impact of environmental variables in the index over ten years

Country ϒ’ τ’ ϕ’ ζ’
China 0,019 0,104 0,100 0,078
USA 0,051 0,005 0,012 0,029

The area of the square (Desirableland), corresponding to the figure 2 is equal to 1. Now, we calculate the representative areas for the USA and China, given by expression (6).

Table 5: Magic Square’s areas

Index of Economic Welfare and Sustainability(% change)
Country 2002-2003 2011-2012
China 1,00 83,47
USA 7,00 37,75

Considering the growth rate of the index in ten years, we obtain:


(∆A^’)/∆t = (83,47-1,00)/10 = 8, 24%/year


(∆A^’)/∆t= (37,75-7,00)/10= 3, 07%/year

Now, in Figure 3 and 4, we can visualize the results obtained through Kaldor’s Magic Square.


In table 4, we note that China obtained results more impressive than the USA in majority of the variables. Analyzing HDI and WATSAN, the Asian country has performed very well ( ϕ’=0,100; τ’=0,104), which is a considerable leap forward in the social area. In compliance with the United Nations Development Program (UNDP), this social improvement occurred due to the significant economic growth that was achieved, especially, the income per capita. Moreover, it appears that governmental support and political willingness became the main driving force to improve the water and sanitation services.

“It is not just an economic question of increasing ef ciency (productivity) in order to guarantee growth, distribution and accumulation of capital. The new paradigm requires the much larger dimension of the socioeconomic process and its sustainability.”

The USA also had a good performance in these indicators ( ϕ’= 0,012; τ’= 0,005). Since 2002, the USA has shown improvements in all areas including the HDI. Furthermore, it has one of the best systems of basic sanitation in the planet. According to the World Bank, almost all citizens have access to treated drinking water and piped sewage.

In relation to SHARENEW, China ( ζ’= 0,078) and the USA( ζ’= 0,029) made onlylittle progress in ten years. The Chinese environmental commitment is based on geopolitical and other factors. The country became a major consumer of petroleum. Consequently, the dependency on imported fossil fuels has increased, which is always a risk in the context of an emergent country. Moreover, the consumption of oil and, especially, coal has been creating negative consequences domestically. The number of cases of respiratory diseases in China’s big cities has been growing exponentially because of the air pollution caused by the burning of coal. To solve these problems, the government is investing substantially in renewable sources of energy. This reality is captured in China’s result for CO2CAP ( ϒ’= 0,019). On the other hand, the USA reduced their C02 emissions significantly in the last ten years, which can be observed in the CO2CAP result ( ϒ’= 0,051). According to the U.S. Energy Information Administration (EIA), the country recently started the transition to a low-carbon economy. One example of the new measures put into place by the government was the switch from coal to natural gas in energy production.

† Notice that, the USA and China, after a long period of almost secret negotiations, announced, in November 2014, in Beijing, an unprecedented compromise towards the reduction of pollutant gases in an effort to conclude a global agreement on climate change in 2015. However, there is a strong domestic tendency in both countries to postpone such objectives. Anyway, it’s better to be pessimistic in this matter, since the result of the agreement will possibly be valid only after 2030 in China and 2025 in the USA.
‡ Notice that in the configuration of the empirical data, we changed the expression Wonderland to Desirableland, due to the fact that the first is an ideal vision and the second is only concerned with the potential performance in given historical circumstances.
§ This technique is related to the Delphi approach, mainly developed by Dalkey & Helmer (1963), for achieving convergence of opinions concerning real-world knowledge solicited from experts. This led to a mathematical structure—the graph theory.

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