Monetary economics from econophysics perspective

This is an invited article for the Discussion and Debate special issue of The European Physical Journal Special Topics on the subject "Can Economics Be a Physical Science?" The first part of the paper traces the personal path of the author from theoretical physics to economics. It briefly summarizes applications of statistical physics to monetary transactions in an ensemble of economic agents. It shows how a highly unequal probability distribution of money emerges due to irreversible increase of entropy in the system. The second part examines deep conceptual and controversial issues and fallacies in monetary economics from econophysics perspective. These issues include the nature of money, conservation (or not) of money, distinctions between money vs. wealth and money vs. debt, creation of money by the state and debt by the banks, the origins of monetary crises and capitalist profit. Presentation uses plain language understandable to laypeople and may be of interest to both specialists and general public.Comment: 23 pages, 1 figur

Low-Carbon Transition Risks for Finance

Mitigating climate change requires information about the inequality in energy consumption. Recent contributions (Banerjee and Yakovenko, 2010; Lawrence et al., 2013; Yakovenko, 2010, 2013) have studied energy inequality through the lens of maximum entropy. They claim a weighted international distribution of total primary energy demand should approach a Boltzmann-Gibbs maximum entropy equilibrium distribution in the form of an exponential distribution, implying convergence to a Gini coefficient of 0.5 from above. The present paper challenges the validity of this claim and critically discusses the applicability of statistical equilibrium reasoning to economics from the viewpoint of social accounting. It is shown that the exponential distribution is only a robust candidate for a statistical equilibrium of energy inequality when employing one particular accounting convention for energy flows, the substitution method. But this method has become problematic with a higher renewable share in the international energy mix, and no other accounting method supports the claim of a convergence to a 0.5 Gini. We conclude that the findings based on maximum entropy reasoning are sensitive to accounting conventions and critically discuss the epistemological implications of this sensitivity for the use of maximum entropy approaches in social sciences

The relationship between income ınequality and energy consumption: a pareto optimal approach

This paper analyzes the relationship between income distribution and energy consumption from a Pareto optimal approach. For this purpose, the causality relationship between electricity consumption per capita (kWh) with respect to country groups and energy consumption per capita (kg of oil equivalent) along with gross domestic product per capita was analyzed. In addition to this purpose, a Pareto analysis was conducted to determine the countries with the highest per capita national income, how much of the world total energy they consume, and whether the law of power in the energy and electricity markets exists. Finally, the impact of official development assistance provided to low-income countries by high-income countries on the low-income countries’ electricity and energy consumption was analyzed. In other words, it was questioned whether pareto redistribution policies serve the purpose or not. The Engle-Granger causality approach was used in the analysis of the causality relationship between variables. Our analysis indicated that, first, the energy data of the country groups may be inadequate in revealing income inequalities. Second, the existence of Pareto law of power and global income inequality can be explained based on energy data. Finally, Pareto optimal redistribution policies to eliminate income inequality remain inadequate in practice

Evolution of the global inequality in greenhouse gases emissions using multidimensional generalized entropy measures.

Given the cumulative consequences of climate change, global concentration of greenhouse gases (GHGs) must be reduced; being inequality in per-capita emissions levels a problem to achieve a commitment by all countries. Thus, the evolution of carbon dioxide (CO2) emissions inequality has received special attention because CO2 is the most abundant GHG in the atmosphere. However, it is necessary to consider other gases to provide a real illustration of our starting point to achieve a multilateral agreement. In this paper, we study the evolution of global inequality in GHGs emissions during the period 1990–2011, considering the four main gases: CO2, methane (CH4), nitrous oxide (N2O) and fluorinated gases (F-gases). The data used in this analysis is taken from the World Resources Institute (2014) and the groups of countries are constructed according to the quantity of emissions that each country released into the atmosphere in the first year of study. For this purpose we use the multidimensional generalized entropy measures proposed by Maasoumi (1986) that can be decomposable into the between- and within-group inequality components. The biggest fall in inequality is observed when we attach more weight to the emissions transfers between the most polluting countries and assume a low substitution degree among pollutants. Finally, some economic policy implications are commented.The authors thank the Ministerio de Economía y Competitividad (Project ECO2013- 48326-C2-2-P) and the Ministerio de Educación, Cultura y Deporte (FPU13/02155) for the partial support of this work

Impacts of poverty alleviation on national and global carbon emissions

Wealth and income are disproportionately distributed among the global population. This has direct consequences on consumption patterns and consumption-based carbon footprints, resulting in carbon inequality. Due to persistent inequality, millions of people still live in poverty today. On the basis of global expenditure data, we compute country- and expenditure-specific per capita carbon footprints with unprecedented details. We show that they can reach several hundred tons of CO2 per year, while the majority of people living below poverty lines have yearly carbon footprints of less than 1 tCO2. Reaching targets under United Nations Sustainable Development Goal 1, lifting more than one billion people out of poverty, leads to only small relative increases in global carbon emissions of 1.6–2.1% or less. Nevertheless, carbon emissions in low- and lower-middle-income countries in sub-Saharan Africa can more than double as an effect of poverty alleviation. To ensure global progress on poverty alleviation without overshooting climate targets, high-emitting countries need to reduce their emissions substantially

Inequality in Energy Consumption: Statistical Equilibrium or a Question of Accounting Conventions?

Understanding inequality energy consumption at the global level delivers key insights for strategies to mitigate climate change. Recent contributions [4, 28, 48, 49] have studied energy inequality through the lens of maximum entropy. They claim a weighted international distribution of total primary energy demand should approach a Boltzmann-Gibbs maximum entropy equilibrium distribution in the form of an exponential distribution. This implies convergence to a Gini coefficient of 0.5 from above. The present paper challenges the validity of this claim and critically discusses the applicability of statistical equilibrium reasoning to economics from the viewpoint of social accounting. It is shown that the exponential distribution is only a robust candidate for a statistical equilibrium of energy inequality when employing one particular accounting convention for energy flows, the substitution method. But this method has become problematic with a higher renewable share in the international energy mix, and no other accounting method supports the claim of a convergence to a 0.5 Gini. We conclude that the findings based on maximum entropy reasoning are sensitive to accounting conventions and critically discuss the epistemological implications of this sensitivity for the use of maximum entropy approaches in social sciences