“…Remarkably, from lambda around 0.1 (10% of tax rate) and below, the Gini index increases abruptly, independently of the targeted population. The results shown in figure 2 are similar to those obtained in [26] (with random values of the risk factors), although numerically different. Figure 2(a) Equilibrium Gini index as a function of the tax rate λ and the fraction of poorest agents p.…”
Section: Taxation With Target Redistributionsupporting
confidence: 77%
“…For that purpose, we use the Yard–Sale model for the exchange among economic agents. In a recent contribution of some of us [26], the effect of taxes on the wealth distribution was studied with individual risk factors ri chosen at random at each exchange. Here we adopt a model where risk factors are uniformly distributed in the interval false[0,1false] given as initial conditions that remain fixed along time.…”
Section: Taxation With Target Redistributionmentioning
confidence: 99%
“…Restraining the scope to conservative and efficient (fair) exchange market models, different rules of interaction have been applied to overcome condensation; for example, increasing the probability of favouring the less wealthy agent in a transaction [11,12] or introducing a taxation mechanism [23][24][25][26], where periodically all agents pay taxes, and the amount collected is shared among a fraction or the totality of them.…”
Section: Introductionmentioning
confidence: 99%
“…In this contribution, we concentrate on the study of this second approach. In a previous work [26], some of us have studied the effect of taxes in the redistribution of wealth; however, agents are obliged to participate passively. They are not allowed to optimize their earnings.…”
Genetic machine learning (ML) algorithms to train agents in the Yard–Sale model proved very useful for finding optimal strategies that maximize their wealth. However, the main result indicates that the more significant the fraction of rational agents, the greater the inequality at the collective level. From social and economic viewpoints, this is an undesirable result since high inequality diminishes liquidity and trade. Besides, with very few exceptions, most agents end up with zero wealth, despite the inclusion of rational behaviour. To deal with this situation, here we include a taxation–redistribution mechanism in the ML algorithm. Previous results show that simple regulations can considerably reduce inequality if agents do not change their behaviour. However, when considering rational agents, different types of redistribution favour risk-averse agents, to some extent. Even so, we find that rational agents looking for optimal wealth can always arrive to an optimal risk, compatible with a particular choice of parameters, but increasing inequality.
This article is part of the theme issue ‘Kinetic exchange models of societies and economies’.
“…Remarkably, from lambda around 0.1 (10% of tax rate) and below, the Gini index increases abruptly, independently of the targeted population. The results shown in figure 2 are similar to those obtained in [26] (with random values of the risk factors), although numerically different. Figure 2(a) Equilibrium Gini index as a function of the tax rate λ and the fraction of poorest agents p.…”
Section: Taxation With Target Redistributionsupporting
confidence: 77%
“…For that purpose, we use the Yard–Sale model for the exchange among economic agents. In a recent contribution of some of us [26], the effect of taxes on the wealth distribution was studied with individual risk factors ri chosen at random at each exchange. Here we adopt a model where risk factors are uniformly distributed in the interval false[0,1false] given as initial conditions that remain fixed along time.…”
Section: Taxation With Target Redistributionmentioning
confidence: 99%
“…Restraining the scope to conservative and efficient (fair) exchange market models, different rules of interaction have been applied to overcome condensation; for example, increasing the probability of favouring the less wealthy agent in a transaction [11,12] or introducing a taxation mechanism [23][24][25][26], where periodically all agents pay taxes, and the amount collected is shared among a fraction or the totality of them.…”
Section: Introductionmentioning
confidence: 99%
“…In this contribution, we concentrate on the study of this second approach. In a previous work [26], some of us have studied the effect of taxes in the redistribution of wealth; however, agents are obliged to participate passively. They are not allowed to optimize their earnings.…”
Genetic machine learning (ML) algorithms to train agents in the Yard–Sale model proved very useful for finding optimal strategies that maximize their wealth. However, the main result indicates that the more significant the fraction of rational agents, the greater the inequality at the collective level. From social and economic viewpoints, this is an undesirable result since high inequality diminishes liquidity and trade. Besides, with very few exceptions, most agents end up with zero wealth, despite the inclusion of rational behaviour. To deal with this situation, here we include a taxation–redistribution mechanism in the ML algorithm. Previous results show that simple regulations can considerably reduce inequality if agents do not change their behaviour. However, when considering rational agents, different types of redistribution favour risk-averse agents, to some extent. Even so, we find that rational agents looking for optimal wealth can always arrive to an optimal risk, compatible with a particular choice of parameters, but increasing inequality.
This article is part of the theme issue ‘Kinetic exchange models of societies and economies’.
“…Social and economic inequalities (Iglesias, Cardoso & Gonçalves, 2021) are complex unresolved problems of our time. The problem is the transfer of this type of inequality to the field of education and science.…”
The article reflects the key problems of humanitarian-scientific discourse characteristic of the modern educational environment. Sociocultural realities dictate new rules and conditions for the development of all spheres of social activity. The educational and scientific sphere is no exception, as a rule, which is rather vulnerable to various types of transformations. Globalization of the current civilizational progress as a strategic constant and a short-term, but significant impact on the values of society associated with the pandemic COVID-19 - had a direct impact on the processes in education and science. At present, the issues of transforming certain attitudes that will allow not to lose the educational-scientific potential, but to continue its development already in the new conditions are actualized. Among the fundamental shifts in the humanitarian sphere of modernity, we note increasing dynamism of educational process and scientific research (linear thinking demonstrates an inability to respond quickly to changes), the actualization of interdisciplinary discourse (challenges facing society are complex in their essence and to solve them. based on the integration of scientific knowledge), the influence of informatization of education and science on humanitarian and moral standards of these branches (application of new information and computer technologies.The article aims to develop a clear system of methodologically axiological settings in modern humanitarian-scientific discourse. The general scientific methodology was used to achieve the set tasks. Using the method of analysis, the main criteria for the proposed attitudes have been achieved. The philosophical-scientific methods of synergetics and dialectics allow evaluating the results and problem aspects of the implementation of value orientations to the humanitarian discourse of today.Practical elements of the obtained results of the article can be used as methodological recommendations for the working curricula at all educational levels and value components of scientific research. Consequently, dynamism, interdisciplinarity, integration, informatization, and humanization are the attitudes that contribute to the functioning of an effective system of education and science both in the global-civilization dimension and in the national-identity dimension.
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