Artikel
The human development index as isoelastic GDP: Evidence from China and Pakistan
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.
- Sprache
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Englisch
- Erschienen in
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Journal: Economies ; ISSN: 2227-7099 ; Volume: 6 ; Year: 2018 ; Issue: 2 ; Pages: 1-9 ; Basel: MDPI
- Klassifikation
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Wirtschaft
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
Multiple or Simultaneous Equation Models: Classification Methods; Cluster Analysis; Principal Components; Factor Models
Index Numbers and Aggregation; Leading indicators
Macroeconomics: Consumption; Saving; Wealth
Money Supply; Credit; Money Multipliers
International Relations, National Security, and International Political Economy: General
Economic Impacts of Globalization: Macroeconomic Impacts
Economic Impacts of Globalization: Economic Development
General Welfare; Well-Being
- Thema
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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
- Ereignis
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Geistige Schöpfung
- (wer)
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Bechtel, Gordon
- Ereignis
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Veröffentlichung
- (wer)
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MDPI
- (wo)
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Basel
- (wann)
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2018
- DOI
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doi:10.3390/economies6020032
- Handle
- Letzte Aktualisierung
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10.03.2025, 11:44 MEZ
Datenpartner
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Objekttyp
- Artikel
Beteiligte
- Bechtel, Gordon
- MDPI
Entstanden
- 2018