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Carl‐Johan Dalgaard, H. Strulik (2011)
Energy distribution and economic growthResource and Energy Economics, 33
B. Dolgonosov (2016)
Knowledge production and world population dynamicsTechnological Forecasting and Social Change, 103
(2015)
Population Division. World Population Prospects, the 2015 Revision
M. Newman (2004)
Power laws, Pareto distributions and Zipf's lawContemporary Physics, 46
WH Greene (1997)
Econometric Analysis
V. Gorshkov, V. Gorshkov, V. Danilov-Danil’yan, K. Losev, A. Makar’eva (1999)
BIOTIC CONTROL OF THE ENVIRONMENTRussian Journal of Ecology, 30
(2016)
Income Distribution and Poverty. Gini (disposable income
P. Edwards (1992)
GENLN2: A general line-by-line atmospheric transmittance and radiance model. Version 3.0: Description and users guide
Oded Galor, D. Weil (1998)
Population, Technology, and Growth: From Malthusian Stagnation to the Demographic Transition and BeyondThe American Economic Review, 90
S. Lawrence, Qin Liu, V. Yakovenko (2013)
Global Inequality in Energy Consumption from 1980 to 2010Entropy, 15
(2017)
Carbon Dioxide Information Analysis Center
R. Coelho, P. Richmond, J. Barry, S. Hutzler (2007)
Double power laws in income and wealth distributionsPhysica A-statistical Mechanics and Its Applications, 387
(2005)
An adiabatic theory of the greenhouse effect
Paul Burke, Shahiduzzaman, D. Stern (2015)
Carbon Dioxide Emissions in the Short Run: The Rate and Sources of Economic Growth MatterEnvironmental Economics eJournal
F. Clementia, T. Matteob, M. Gallegatic (2006)
The power-law tail exponent of income distributions
A. Silva, V. Yakovenko (2004)
Temporal evolution of the "thermal" and "superthermal" income classes in the USA during 1983-2001EPL, 69
Jiandong Chen, Fuqian Fang, W. Hou, Fengying Li, Ming Pu, M. Song (2015)
Chinese Gini Coefficient from 2005 to 2012, Based on 20 Grouped Income Data Sets of Urban and Rural ResidentsERN: Quality of Life & Environmental Comparisons (Topic)
G. Stephens, D. O'Brien, P. Webster, P. Pilewski, S. Kato, Juilin Li (2015)
The albedo of EarthReviews of Geophysics, 53
A. Jarvis, S. Jarvis, C. Hewitt (2015)
Resource acquisition, distribution and end-use efficiencies and the growth of industrial societyEarth System Dynamics Discussions, 6
Oded Galor, Omer Moav (2002)
From Physical to Human Capital Accumulation: Inequality in the Process of DevelopmentEconomic History
V. Yakovenko, J. Rosser (2009)
Colloquium: Statistical mechanics of money, wealth, and incomeReviews of Modern Physics, 81
B. Dolgonosov (2010)
On the reasons of hyperbolic growth in the biological and human world systemsEcological Modelling, 221
A. Drăgulescu, V. Yakovenko (2001)
Exponential and power-law probability distributions of wealth and income in the United Kingdom and the United StatesPhysica A-statistical Mechanics and Its Applications, 299
J. Holdren (1991)
Population and the energy problemPopulation and Environment, 12
S. Lozano, E. Gutiérrez (2008)
Non-parametric frontier approach to modelling the relationships among population, GDP, energy consumption and CO2 emissionsEcological Economics, 66
(2004)
Temporal evolution of the “thermal” and “superthermal” income classes in the USA during 1983–2001
(2017)
Income inequality. I.5. Global income inequality
G. Myhre, F. Stordal (1997)
Role of spatial and temporal variations in the computation of radiative forcing and GWPJournal of Geophysical Research, 102
(2016)
The World Factbook. Gini index
G. Myhre, E. Highwood, K. Shine, F. Stordal (1998)
New estimates of radiative forcing due to well mixed greenhouse gasesGeophysical Research Letters, 25
R. Ramanathan (2006)
A multi-factor efficiency perspective to the relationships among world GDP, energy consumption and carbon dioxide emissionsTechnological Forecasting and Social Change, 73
(2014)
Global CO 2 yearly IPCC (2001) WGI. The scientific basis
Y. Fujiwara, W. Souma, H. Aoyama, T. Kaizoji, M. Aoki (2002)
Growth and fluctuations of personal incomePhysica A-statistical Mechanics and Its Applications, 321
N. Grosjean, T. Huillet (2016)
Deterministic versus stochastic aspects of superexponential population growth modelsPhysica A-statistical Mechanics and Its Applications, 455
BM Dolgonosov (2009)
Nonlinear dynamics of ecological and hydrological processes
Tomas Hellebrandt, P. Mauro (2015)
The Future of Worldwide Income DistributionEconometric Modeling: Macroeconomics eJournal
(1998)
EPJ manuscript No.
S. Yitzhaki, E. Schechtman (2013)
More Than a Dozen Alternative Ways of Spelling Gini
Ping-Yu Chen, Sheng-Tung Chen, Chia-Sheng Hsu, Chi-Chung Chen (2016)
Modeling the global relationships among economic growth, energy consumption and CO2 emissionsRenewable & Sustainable Energy Reviews, 65
(1997)
Econometric Analysis, 3rd edn. Prentice-Hall, Upper Saddle River
S. Puliafito, J. Puliafito, M. Grand (2008)
Modeling population dynamics and economic growth as competing species: An application to CO2 global emissionsEcological Economics, 65
A Drăgulescu, VM Yakovenko (2001)
Evidence for the exponential distribution of income in the USAEur Phys J B, 20
O Galor, O Moav (2004)
From physical to human capital accumulation: Inequality and the process of developmentRev Econ Stud, 71
E. Schechtman, S. Yitzhaki (2012)
The Gini Methodology: A Primer on a Statistical Methodology
L. Lehmann, M. Feldman (2009)
Coevolution of adaptive technology, maladaptive culture and population size in a producer–scrounger gameProceedings of the Royal Society B: Biological Sciences, 276
PJ Burke, Md Shahiduzzaman, DI Stern (2015)
Carbon dioxide emissions in the short run: the rate and sources of economic growth matterGlob Environ Change, 33
The work is aimed at developing a conceptual model of the relationship among global indicators such as world population, GDP, primary energy consumption, anthropogenic carbon dioxide emissions, and mean surface temperature anomaly. The world economy is viewed from three perspectives as (1) a manufacturing system that consumes energy and returns a product; (2) a climate-active system that shifts the planetary thermal equilibrium due to greenhouse gas emissions; and (3) a resource-distributed system in which the generalized resource is distributed among consumers of different scale and can be equivalently expressed in both monetary and energy units. It was established that dependencies between the indicators are power law: temperature anomaly increases proportionally to cumulative energy consumption, GDP grows in proportion to the product of current and cumulative energy consumption raised to a power of less than unity, and energy consumption in turn is a power-law function of population with the exponent being expressed through the Gini coefficient, which is a measure of the inequality in income distribution on a global scale. Parameters of these dependencies were determined using a special procedure of fitting to empirical data. It was found that energy consumption, temperature anomaly, and GDP grow over the industrial period in proportion to population raised to a power close to 1.5, 1.8, and 2, respectively.
BioPhysical Economics and Resource Quality – Springer Journals
Published: Mar 13, 2018
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