Measuring environmental degradation by using principal component analysis

The objective of the paper is to measure environmental degradation on the basis of some selected indicators by the application of a simple multivariate technique known as Principal Component Analysis. For this purpose the study considered six variables, namely, GDP per capita, fuel consumption, total fertility rate, water supply, sanitation, and electricity. However, because of unavailability of data, the variables such as technology relating to environment, waste disposal, air pollution, women/gender issues relating to environment, corruption, democracy etc. could not be considered. The results show that principal components explain about 62% of the variations in the level of environmental degradation. The variables like GDP per capita, fuel consumption, water supply and electricity played a major role in classifying the countries in terms of environmental degradation compared to the variables, sanitation and total fertility rate. The findings show that countries which have high GDP per capita, low fuel consumption, higher percentage of people having access to water supply and sanitation as well as electricity ranked higher in terms of environmental quality despite high fertility rate as shown by the spectacular example of Saudi Arabia. By contrast, those countries which have low percentage of population having access to safe water and sanitation as well as electricity, high fuel consumption and high fertility were ranked lower in terms of environmental quality despite high per capita income, as shown by the example of Angola which is placed in lowest position among the 51 selected countries. The results also show that correlation between poverty and environmental degradation is particularly acute in African countries where high population growth is acting as an exacerbating factor. The study concluded that high fertility has much impact on environmental degradation in case of poorer countries than in case of rich countries.

Tahmina KhatunEmail: