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A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Statistical Physics".

Deadline for manuscript submissions: closed (22 June 2023) | Viewed by 12055

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Prof. José Roberto Iglesias

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1. Instituto de Física, Universidade Federal do Rio Grande do Sul, Porto Alegre 91501-970, RS, Brazil
2. Instituto Nacional de Ciência e Tecnologia de Sistemas Complexos, CBPF, Rio de Janeiro 22290-180, RJ, Brazil
Interests: physics; complex systems; Kondo systems; econophysics

Special Issue Information

Dear Colleagues,

The application of statistical physics techniques in complex collective behavior problems is one of the most developed multidisciplinary areas and has been very successful in the analysis of various social and economic behaviors. The objective of this Special Issue is to put together different contributions using analytical methods, numerical simulations, machine learning, etc., to examine models that explicitly consider the interactions between individuals and their learning capacities, as well as analyze the emergence of collective social behaviors. It is interesting to determine the interdependence between individual decisions and collective behavior, as well as their consequences: opinion dynamics, respect or not to social rules, emerging behaviors in time and space, formation and dissemination of behaviors and, very important, the proposal of policies to be adopted in the face of certain economic and social problems. The effect of an outside intervention on group dynamics (e.g., advertising, fashions, state interference, tax effect, or simply a dynamic that privileges certain groups or individuals) should also be considered. The particular subjects to be addressed in the proposed volume are:

The distribution of wealth and inequality, as well as the mechanisms of wealth redistribution, effect of taxes,
Market dynamics, herding phenomena,
The adoption of new technologies and the diffusion of fashions,
The adoption of cooperative and/or altruistic social behaviors,
Collective behavior in traffic, including the study of autonomous vehicles,
Dynamics and propagation of opinions,
Epidemics and effect of vaccination,
Complex networks and adaptative complex networks,
Criminality: economic consequences of criminality,
Economic consequences of ignoring simple rules or norms,
Other multidisciplinary problems studied within statistical physics.

Prof. Dr. José Roberto Iglesias
Guest Editor

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

complex systems
econophysics
sociophysics
markets
inequalities and wealth distribution
taxes and redistribution
cooperative behavior
epidemics, opinion dynamics

Published Papers (10 papers)

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Research

21 pages, 948 KiB

Open AccessArticle

Looking into the Market Behaviors through the Lens of Correlations and Eigenvalues: An Investigation on the Chinese and US Markets Using RMT

by Yong Tang, Jason Xiong, Zhitao Cheng, Yan Zhuang, Kunqi Li, Jingcong Xie and Yicheng Zhang

Entropy 2023, 25(10), 1460; https://doi.org/10.3390/e25101460 - 18 Oct 2023

Viewed by 1177

Abstract

This research systematically analyzes the behaviors of correlations among stock prices and the eigenvalues for correlation matrices by utilizing random matrix theory (RMT) for Chinese and US stock markets. Results suggest that most eigenvalues of both markets fall within the predicted distribution intervals by RMT, whereas some larger eigenvalues fall beyond the noises and carry market information. The largest eigenvalue represents the market and is a good indicator for averaged correlations. Further, the average largest eigenvalue shows similar movement with the index for both markets. The analysis demonstrates the fraction of eigenvalues falling beyond the predicted interval, pinpointing major market switching points. It has identified that the average of eigenvector components corresponds to the largest eigenvalue switch with the market itself. The investigation on the second largest eigenvalue and its eigenvector suggests that the Chinese market is dominated by four industries whereas the US market contains three leading industries. The study later investigates how it changes before and after a market crash, revealing that the two markets behave differently, and a major market structure change is observed in the Chinese market but not in the US market. The results shed new light on mining hidden information from stock market data. Full article

(This article belongs to the Special Issue Statistical Physics and Its Applications in Economics and Social Sciences)

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21 pages, 3590 KiB

Open AccessArticle

A Social Recommendation Model Based on Basic Spatial Mapping and Bilateral Generative Adversarial Networks

by Suqi Zhang, Ningjing Zhang, Wenfeng Wang, Qiqi Liu and Jianxin Li

Entropy 2023, 25(10), 1388; https://doi.org/10.3390/e25101388 - 28 Sep 2023

Viewed by 662

Abstract

Social recommender systems are expected to improve recommendation quality by incorporating social information when there is little user–item interaction data. Therefore, how to effectively fuse interaction information and social information becomes a hot research topic in social recommendation, and how to mine and exploit the heterogeneous information in the interaction and social space becomes the key to improving recommendation performance. In this paper, we propose a social recommendation model based on basic spatial mapping and bilateral generative adversarial networks (MBSGAN). First, we propose to map the base space to the interaction and social space, respectively, in order to overcome the issue of heterogeneous information fusion in two spaces. Then, we construct bilateral generative adversarial networks in both interaction space and social space. Specifically, two generators are used to select candidate samples that are most similar to user feature vectors, and two discriminators are adopted to distinguish candidate samples from high-quality positive and negative examples obtained from popularity sampling, so as to learn complex information in the two spaces. Finally, the effectiveness of the proposed MBSGAN model is verified by comparing it with both eight social recommendation models and six models based on generative adversarial networks on four public datasets, Douban, FilmTrust, Ciao, and Epinions. Full article

(This article belongs to the Special Issue Statistical Physics and Its Applications in Economics and Social Sciences)

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9 pages, 654 KiB

Open AccessArticle

Taxes, Inequality, and Equal Opportunities

by José Roberto Iglesias, Ben-Hur Francisco Cardoso and Sebastián Gonçalves

Entropy 2023, 25(9), 1346; https://doi.org/10.3390/e25091346 - 16 Sep 2023

Viewed by 806

Abstract

Extreme inequality represents a grave challenge for impoverished individuals and poses a threat to economic growth and stability. Despite the fulfillment of affirmative action measures aimed at promoting equal opportunities, they often prove inadequate in effectively reducing inequality. Mathematical models and simulations have demonstrated that even when equal opportunities are present, wealth tends to concentrate in the hands of a privileged few, leaving the majority of the population in dire poverty. This phenomenon, known as condensation, has been shown to be an inevitable outcome in economic models that rely on fair exchange. In light of the escalating levels of inequality in the 21st century and the significant state intervention necessitated by the recent COVID-19 pandemic, an increasing number of scholars are abandoning neo-liberal ideologies. Instead, they propose a more robust role for the state in the economy, utilizing mechanisms such as taxation, regulation, and universal allocations. This paper begins with the assumption that state intervention is essential to effectively reduce inequality and to revitalize the economy. Subsequently, it conducts a comparative analysis of various taxation and redistribution mechanisms, with a particular emphasis on their impact on inequality indices, including the Gini coefficient. Specifically, it compares the effects of fortune and consumption-based taxation, as well as universal redistribution mechanisms or targeted redistribution mechanisms aimed at assisting the most economically disadvantaged individuals. The results suggest that fortune taxation are more effective than consumption-based taxation to reduce inequality. Full article

(This article belongs to the Special Issue Statistical Physics and Its Applications in Economics and Social Sciences)

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19 pages, 11607 KiB

Open AccessArticle

A Wealth Distribution Agent Model Based on a Few Universal Assumptions

by Matheus Calvelli and Evaldo M. F. Curado

Entropy 2023, 25(8), 1236; https://doi.org/10.3390/e25081236 - 19 Aug 2023

Viewed by 997

Abstract

We propose a new agent-based model for studying wealth distribution. We show that a model that links wealth to information (interaction and trade among agents) and to trade advantage is able to qualitatively reproduce real wealth distributions, as well as their evolution over time and equilibrium distributions. These distributions are shown in four scenarios, with two different taxation schemes where, in each scenario, only one of the taxation schemes is applied. In general, the evolving end state is one of extreme wealth concentration, which can be counteracted with an appropriate wealth-based tax. Taxation on annual income alone cannot prevent the evolution towards extreme wealth concentration. Full article

(This article belongs to the Special Issue Statistical Physics and Its Applications in Economics and Social Sciences)

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11 pages, 1135 KiB

Open AccessArticle

Kinetic Models of Wealth Distribution with Extreme Inequality: Numerical Study of Their Stability against Random Exchanges

by Asim Ghosh, Suchismita Banerjee, Sanchari Goswami, Manipushpak Mitra and Bikas K. Chakrabarti

Entropy 2023, 25(7), 1105; https://doi.org/10.3390/e25071105 - 24 Jul 2023

Cited by 1 | Viewed by 1169

Abstract

In view of some recent reports on global wealth inequality, where a small number (often a handful) of people own more wealth than 50% of the world’s population, we explored if kinetic exchange models of markets could ever capture features where a significant fraction of wealth can concentrate in the hands of a few as the market size N approaches infinity. One existing example of such a kinetic exchange model is the Chakraborti or Yard-Sale model; in the absence of tax redistribution, etc., all wealth ultimately condenses into the hands of a single individual (for any value of N), and the market dynamics stop. With tax redistribution, etc., steady-state dynamics are shown to have remarkable applicability in many cases in our extremely unequal world. We show that another kinetic exchange model (called the Banerjee model) has intriguing intrinsic dynamics, where only ten rich traders or agents possess about 99.98% of the total wealth in the steady state (without any tax, etc., like external manipulation) for any large N value. We will discuss the statistical features of this model using Monte Carlo simulations. We will also demonstrate that if each trader has a non-zero probability f of engaging in random exchanges, then these condensations of wealth (e.g., 100% in the hand of one agent in the Chakraborti model, or about 99.98% in the hands of ten agents in the Banerjee model) disappear in the large N limit. Moreover, due to the built-in possibility of random exchange dynamics in the earlier proposed Goswami–Sen model, where the exchange probability decreases with the inverse power of the wealth difference between trading pairs, one does not see any wealth condensation phenomena. In this paper, we explore these aspects of statistics of these intriguing models. Full article

(This article belongs to the Special Issue Statistical Physics and Its Applications in Economics and Social Sciences)

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21 pages, 6070 KiB

Open AccessArticle

Productivity vs. Evenness in the U.S. Financial Market: A Business Ecosystem Perspective

by Hugo Fort

Entropy 2023, 25(7), 1029; https://doi.org/10.3390/e25071029 - 07 Jul 2023

Viewed by 993

Abstract

This paper starts by presenting an empirical finding in the U.S. stock market: Between 2001 and 2021, high productivity was achieved when the Shannon evenness—measuring the inverse of concentration—dropped. Conversely, when the Shannon evenness soared, productivity plunged. The same inverse relationship between evenness and productivity has been observed in several ecosystems. This suggests explaining this result by adopting the business ecosystem perspective, i.e., regarding the tangle of interactions between companies as an ecological network, in which companies play the role of species. A useful strategy to model such ecological communities is through ensembles of synthetic communities of pairwise interacting species, whose dynamics is described by the Lotka–Volterra generalized equations. Each community is specified by a random interaction matrix whose elements are drawn from a uniform distribution centered around 0. It is shown that the inverse relationship between productivity and evenness can be generated by varying the strength of the interaction between companies. When the strength increases, productivity increases and simultaneously the market evenness decreases. Conversely, when the strength decreases, productivity decreases and evenness increases. This strength can be interpreted as reflecting the looseness of monetary policy, thus providing a link between interest rates and market structure. Full article

(This article belongs to the Special Issue Statistical Physics and Its Applications in Economics and Social Sciences)

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27 pages, 2345 KiB

Open AccessArticle

Can the Sci-Tech Innovation Increase the China’s Green Brands Value?—Evidence from Threshold Effect and Spatial Dubin Model

by Xiaofei Zhang, Yang Xiao and Linyu Wang

Entropy 2023, 25(2), 290; https://doi.org/10.3390/e25020290 - 03 Feb 2023

Cited by 2 | Viewed by 1516

Abstract

Based on the perspective of the innovation value chain, sci-tech innovation is divided into two stages: R&D and achievement transformation. This paper uses panel data from 25 provinces in China as the sample. We utilize a two-way fixed effect model, spatial Dubin model, and panel threshold model to discuss the impact of two-stage innovation efficiency on the value of the green brand, the spatial effect of this impact, and the threshold role of intellectual property protection in the process. The results indicate that: (1) the two stages of innovation efficiency have a positive impact on the value of green brands, and the effect of the eastern region is significantly better than that of the central and western regions. (2) The spatial spillover effect of the two stages of regional innovation efficiency on the value of green brands is evident, especially in the eastern region. (3) The innovation value chain has a pronounced spillover effect. (4) The single threshold effect of intellectual property protection is significant. When the threshold is crossed, the positive impact of the two stages of innovation efficiency on the value of green brands is significantly enhanced. (5) The influence of economic development level, openness, market size, and marketization degree on the value of green brands shows remarkable regional differences. In conclusion, this study contributes to understanding green brands’ growth and provides important implications for developing independent brands in various regions of China. Full article

(This article belongs to the Special Issue Statistical Physics and Its Applications in Economics and Social Sciences)

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17 pages, 2855 KiB

Open AccessArticle

Wealth Redistribution and Mutual Aid: Comparison Using Equivalent/Non-Equivalent Exchange Models of Econophysics

by Takeshi Kato

Entropy 2023, 25(2), 224; https://doi.org/10.3390/e25020224 - 24 Jan 2023

Cited by 1 | Viewed by 1410

Abstract

Given wealth inequality worldwide, there is an urgent need to identify the mode of wealth exchange through which it arises. To address the research gap regarding models that combine equivalent exchange and redistribution, this study compares an equivalent market exchange with redistribution based on power centers and a non-equivalent exchange with mutual aid using the Polanyi, Graeber, and Karatani modes of exchange. Two new exchange models based on multi-agent interactions are reconstructed following an econophysics-based approach for evaluating the Gini index (inequality) and total exchange (economic flow). Exchange simulations indicate that the evaluation parameter of the total exchange divided by the Gini index can be expressed by the same saturated curvilinear approximate equation using the wealth transfer rate and time period of redistribution, the surplus contribution rate of the wealthy, and the saving rate. However, considering the coercion of taxes and its associated costs and independence based on the morality of mutual aid, a non-equivalent exchange without return obligation is preferred. This is oriented toward Graeber’s baseline communism and Karatani’s mode of exchange D, with implications for alternatives to the capitalist economy. Full article

(This article belongs to the Special Issue Statistical Physics and Its Applications in Economics and Social Sciences)

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13 pages, 509 KiB

Open AccessArticle

Resource Concentration and Clustering in Replicator Dynamics with Stochastic Reset Events

by Ignacio T. Gómez Garay and Damián H. Zanette

Entropy 2023, 25(1), 99; https://doi.org/10.3390/e25010099 - 03 Jan 2023

Cited by 1 | Viewed by 1047

Abstract

As a model for economic and ecological systems, replicator dynamics represent a basic form of agent competition for finite resources. Here, we investigate the effects of stochastic resetting in this kind of processes. Random reset events abruptly lead individual resources to a small value from which dynamics must start anew. Numerical results show that resource distribution over the population of competing agents develops highly nonuniform profiles, exhibiting clustering and fluctuations with anomalous dependence on the population size. This non-standard statistical behavior jeopardizes an analytical treatment based on mean-field assumptions. We propose alternative simplified analytical approaches which provide a stylized description of entropy evolution for the clustered distribution of resources and explain the unusually slow decrease of fluctuations. Full article

(This article belongs to the Special Issue Statistical Physics and Its Applications in Economics and Social Sciences)

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19 pages, 920 KiB

Open AccessArticle

A Hybrid Opinion Formation and Polarization Model

by Baizhong Yang, Quan Yu and Yi Fan

Entropy 2022, 24(11), 1692; https://doi.org/10.3390/e24111692 - 19 Nov 2022

Viewed by 1311

Abstract

The last decade has witnessed a great number of opinion formation models that depict the evolution of opinions within a social group and make predictions about the evolution process. In the traditional formulation of opinion evolution such as the DeGroot model, an agent’s opinion is represented as a real number and updated by taking a weighted average of its neighbour’s opinions. In this paper, we adopt a hybrid representation of opinions that integrate both the discrete and continuous nature of an opinion. Basically, an agent has a ‘Yes’, ‘Neutral’ or ‘No’ opinion on some issues of interest and associates with its Yes opinion a support degree which captures how strongly it supports the opinion. With such a rich representation, not only can we study the evolution of opinion but also that of support degree. After all, an agent’s opinion can stay the same but become more or less supportive of it. Changes in the support degree are progressive in nature and only a sufficient accumulation of such a progressive change will result in a change of opinion say from Yes to No. Hence, in our formulation, after an agent interacts with another, its support degree is either strengthened or weakened by a predefined amount and a change of opinion may occur as a consequence of such progressive changes. We carry out simulations to evaluate the impacts of key model parameters including (1) the number of agents, (2) the distribution of initial support degrees and (3) the amount of change of support degree changes in a single interaction. Last but not least, we present several extensions to the hybrid and progressive model which lead to opinion polarization. Full article

(This article belongs to the Special Issue Statistical Physics and Its Applications in Economics and Social Sciences)

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