Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/197084 
Authors: 
Year of Publication: 
2018
Citation: 
[Journal:] Economies [ISSN:] 2227-7099 [Volume:] 6 [Issue:] 2 [Publisher:] MDPI [Place:] Basel [Year:] 2018 [Pages:] 1-9
Publisher: 
MDPI, Basel
Abstract: 
Gross domestic product (GDP) is shown to possess three new desiderata. First, GDP is almost perfectly correlated over time with the first principal component of its three classical indicators. Second, this principal component is in a class of weighted indexes ancillary to GDP. Each ancillary index informs policy as to allocation of resources over the three GDP indicators. Third, a country-specific power of GDP almost perfectly predicts the United Nation's Human Development Index (HDI). These findings are brought by principal components and regression analyses of time series supplied by the World Bank and the United Nations. Axiomatic HDI computation is carried out without survey sampling, probabilistic inference, significance testing, or even HDI data.
Subjects: 
societal data theory
country specificity
internal consistency of GDP indicators
latent population distributions
latent 2-level principal-components analysis
Nt-weighted versus weighted GDP indicators
JEL: 
C22
C38
C43
E21
E51
F50
F62
F63
I31
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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