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Do rich countries necessarily have high GHG emissions?

This article deals about the linkage between emitted greenhouse gases and GDP per capita. The GDP per capita at PPP shows very much and is maybe the most important statistic in the Country Scorecard, as it measures the living standard. From a material point of view it is the best available measure. However, it ignores how this living standard is achieved and whether the economy is sustainable. It especially ignores the effect to the environment. In this article we will create a linkage between these two statistics.



For the following statistics I used two statistics provided by the United Nations, which are also shown in the Country Scorecard. First, the GHG emissions per capita are taken. This figure shows how many greenhouse gases (GHG) are emitted by every citizen on average. This statistic includes carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) which account for about 98% of the environmental pressure leading to climate change. The last two gases are translated into CO2 equivalents, as these gases harm the environment more than CO2. The average GHG emissions per capita in CO2-equivalent is 7.0 tonnes with a standard deviation of 6.8 tonnes. The highest value is 47.5 tonnes (Jamaica) and the lowest one is 0.3 tonnes (Burundi). Secondly, the GDP per capita at PPP is taken. This figure shows the income level of the average citizen (per capita means per person) per year. It is used to compare living standards. The higher the value, the better the living standard in that particular country. The average GDP at PPP for the countries which published GHG statistics (in total 134 countries) is 9,894$ with a standard deviation of about 16,000$.
 


Using that data, the GHG emission per 1,000$ GDP per capita can be calculated. This leads to interesting results. While France uses just 0.093 tonnes of CO2 equivalent per 1,000$ GDP, Paraguay uses about 25 tonnes of CO2 equivalent to achieve the same economic performance. Using this method, a ranking can be made.



Another way is to draw a plot-graph. For a better orientation, the graph also shows the mean of the particular statistics (black line). This way, the graph is divided into quadrants.




Source: Own graphic using data provided by the United Nations



As seen above there are very few countries in quadrant I. There are just three countries with an above-average GDP and below-average GHG emissions. These countries are Liechtenstein (not displayed in the graph, as they have a GDP of over 100,000$), France and Monaco. Liechtenstein and Monaco are just very small countries, so the only big country is France. There are 77 countries in quadrant II, 29 in quadrant III and 25 in quadrant IV.



There are very few countries which manage to have a high GDP and emit little GHG emissions. On the other hand, there are very much countries, which have a low GDP, but they have all kinds of GHG emissions, reaching from very low to very high. The following graph will just show the countries in the quadrants II and IV. Additionally, a linear regression has been calculated. As seen in R , there is almost no correlation between GHG emissions and GDP for countries below average GDP.




Source: Own graphic using data provided by the United Nations



The same, and even more, is true, when just taking countries with above average GDP (R =0,0025).




Source: Own graphic using data provided by the United Nations

 

The previous graph answers the question in the heading. There is no correlation between GHG emissions and GDP for rich nations. In contrary, there is even less correlation for richer nations than for poorer countries.

In total, including all data R is 0,113. This means that there is no statistical evidence for a correlation between high living standard and high GHG emissions.
 


To conclude, no statistically significant correlation between GHG emissions and living standard exists. The conclusion of this statement is that it is possible for every country to reduce their GHG emissions to a low level and make the earth cleaner and contribute to measures to reduce the pace of global warming.
 

 


The table following this link will show the detailed data. If you are interested in environmental topics, you may also download my free e-book with the title "Economology". It deals with ecological issues from an economic point of view and concludes that ecology is long-term economy.

 

 

 

It has shortages such as it does not include the black market or non-commercial activities. This topic will not be covered in this article.

The second place France is shown here, as the first place Liechtenstein has unusual figures. Liechtenstein is a small country, with high GDP. However, the per capita GDP is distorted as much of the GDP is contributed by people living outside Liechtenstein. This economic activity will increase the GDP of Liechtenstein, but these people are not included when calculating the GDP per capita. The same is true for the third place Monaco.

R can range between 0 and 1. 1 means perfect correlation, while 0 means no correlation. R is also called "goodness of fit".
 

 
 

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