Abstract
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.
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Notes
Perhaps the most frequently used extraction approach is “root greater than one” criterion. Originally suggested by Kaiser (1958; cited in Dillon and Goldstein 1984), this criterion retains those components whose eigenvalues are greater than one. The rationale for this criterion is that any component should account for more “variance” than any single variable in the standardized test score space (see Dillon and Goldstein 1994, p. 48).
Scores based on six and eight variables have been retained for the purpose of comparison. Scores based on seven variables are not shown as it makes a little or no difference in the case of ranking of countries.
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Acknowledgements
I would like to express my deep gratitude to the Director, Centre for Policy Research (CPR), Universiti Sains Malaysia, for giving me the opportunity to join CPR as a Visiting Research Fellow and conduct my research activities here. I also deeply acknowledge the helpful comments of Dr. Chan Huan Chiang of CPR, Universiti Sains Malaysia, for his helpful comments in writing this paper.
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Khatun, T. Measuring environmental degradation by using principal component analysis. Environ Dev Sustain 11, 439–457 (2009). https://doi.org/10.1007/s10668-007-9123-2
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DOI: https://doi.org/10.1007/s10668-007-9123-2