Principal component analysis: Difference between revisions

Revision as of 09:24, 27 November 2024

Revision as of 11:02, 5 December 2024

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PCA can be used as a formal method for the development of indexes. As an alternative [[confirmatory composite analysis]] has been proposed to develop and assess indexes.<ref>{{cite journal |last1=Schamberger |first1=Tamara |last2=Schuberth |first2=Florian |last3=Henseler |first3=Jörg |title=Confirmatory composite analysis in human development research |journal=International Journal of Behavioral Development |volume=47 |issue=1 |pages=88-100 |doi=10.1177/01650254221117506|hdl=10362/143639 |hdl-access=free }}</ref>

The [[City development index|City Development Index]] was developed by PCA from about 200 indicators of city outcomes in a 1996 survey of 254 global cities. The first principal component was subject to iterative regression, adding the original variables singly until about 90% of its variation was accounted for. The index ultimately used about 15 indicators but was a good predictor of many more variables. Its comparative value agreed very well with a subjective assessment of the condition of each city. The coefficients on items of infrastructure were roughly proportional to the average costs of providing the underlying services, suggesting the Index was actually a measure of effective physical and social investment in the city.

The country-level [[Human Development Index]] (HDI) from [[United Nations Development Programme|UNDP]], which has been published since 1990 and is very extensively used in development studies,<ref>{{Cite web |last=Human Development Reports |title=Human Development Index |url=https://hdr.undp.org/en/content/human-development-index-hdi |access-date=2022-05-06 |website=United Nations Development Programme}}</ref> has very similar coefficients on similar indicators, strongly suggesting it was originally constructed using PCA.