TITLE:
GDP Is Well-Being! Results in the USA and China
AUTHORS:
Gordon Bechtel
KEYWORDS:
Country Specificity of Fractional Polynomial Regressions, Internal Consistency of Keynesian Indicators, 2-Level Principal Components Analysis, Unidimensional Index Theory, Prediction of HDI from Weighted and Unweighted GDP
JOURNAL NAME:
Open Journal of Social Sciences,
Vol.7 No.12,
December
9,
2019
ABSTRACT: This article quality assures GDP and then links it
to well-being in the world’s two largest economies. Despite the global plethora of national indexes, there has been little quality
assurance of the unidimensionality of their component indicators. Unidimensional index theory constructs a weighted composite
from a 2-level principal components
analysis of its several indicators. This weighted composite evaluates
its unweighted counterpart, and informs governments about the allocation of resources over its composite indicators. Two axioms predict that weighted and unweighted indexes are perfectly
correlated over successive yearly populations in the USA and China. Under these
axioms, fractional polynomial regressions of
any criterion on these weighted and unweighted indexes perfectly predict
this criterion. We confirm the unidimensionality of American and
Chinese GDP indexes and their near-perfect prediction of the United Nation’s
Human Development Index (HDI). This application discovers that HDI computation
can be carried out from a nation’s GDP alone, i.e., without survey sampling, questionnaire interrogation, probabilistic
inference, significance testing, or even HDI data.