arXiv subjects

Sebastián Gonçalves

Publications and source records attributed to Sebastián Gonçalves.

15 recordsLinked to original sources

arXiv2025

The Inequity of Consumption-Based Tax Systems

This study examines the lack of redistributive effectiveness of consumption-based tax systems with respect to social fairness. Through numerical simulations, we explore the wealth exchanges among economic agents subject to flat consumption taxes, comparing universal redistribution with optimal targeted approaches. The results demonstrate that consumption taxes exhibit inherent regressivity, disproportionately burdening the poorest 40% of households who contribute over half of total tax revenue for most tax rates. The findings challenge the equity of consumption taxes and provide quantitative insights for designing more fair fiscal policies.

physics.soc-ph↗

arXiv2025

Economic Inequality between Groups in an a priori Stratified Society

We present an agent-based model of economic exchange in a society composed of two groups, representing two social groups and with different internal protection rules for the poor agents. The goal is to address the emerging wealth distribution when economic rules are not the same for all individuals. Individuals exchange wealth in pairwise interactions with no underlying lattice. The wealth, risk aversion factor, and group of the agents characterize their state. The wealth exchanged between two agents obeys a fair rule: the quantities put at stake by them are the same regardless of who wins. One agent can interact with another agent in the same or the other group, controlled by a rate which is a parameter of the model. Inter-group exchanges obey an exclusive protection rule, which can be understood as a public policy to reduce inequality. We show that the most protected group accumulates more wealth, has less inequality, and has higher mobility than the other group. The results of simulations are compared with income distribution in Brazil discriminated by race as an example of the application our model.

physics.soc-ph↗

arXiv2024

Nightclub bar dynamics: statistics of serving times

In this work, we investigate the statistical properties of drink serving in a nightclub bar, utilizing a stochastic model to characterize pedestrian dynamics within the venue. Our model comprises a system of n agents moving across an underlying square lattice of size l representing the nightclub venue. Each agent can exist in one of three states: thirsty, served, or dancing. The dynamics governing the state changes are influenced by a memory time, denoted as τ, which reflects their drinking habits. Agents' movement throughout the lattice is controlled by a parameter α which measures the impetus towards/away from the bar. When α = 0, a power-law distribution emerges due to the non-objectivity of the agents. As α moves into intermediate values, an exponential behavior is observed, as it becomes possible to mitigate the drastic jamming effects in this scenario. However, for higher α values, the power-law distribution resurfaces due to increased jamming. We also demonstrate that the average concentration of served, thirsty, and dancing agents provide a reliable indicator of when the system reaches a jammed state. Subsequently, we construct a comprehensive map of the system's stationary state, supporting the idea that for high densities, α is not relevant, but for lower densities, the optimal values of measurements occurs at high values of α. To complete the analysis, we evaluate the conditional persistence, which measures the probability of an agent failing to receive their drink despite attempting to do so. In addition to contributing to the field of pedestrian dynamics, the present results serve as valuable indicators to assist commercial establishments in providing better services to their clients, tailored to the average drinking habits of their customers.

physics.soc-ph↗

arXiv2023

Effectiveness of wealth-based vs exchange-based tax systems in reducing inequality

In the so-called ``fair'' models of peer-to-peer wealth exchanges, economic inequality tends to reach its maximum value asymptotically. This global trend is evident as the richest continuously accumulate a larger share of wealth at the expense of others. To address the mounting issue of inequality, different strategies of taxes and redistribution are commonly employed. Our study delves into the interplay between wealth and trade (consumption) tax bases, probing their impact on wealth distribution within wealth-conservative economies. The ultimate aim is to unearth an optimal framework that adeptly curbs inequality.Through a meticulous analysis of varying tax rates and the allocation of the collected tax to the most economically vulnerable strata, we unveil a compelling pattern resembling two distinct phases. These phases delineate the most effective systems for inequality mitigation. Our findings underscore the synergistic potential of amalgamating these tax systems, surpassing the individual efficacy of each. This synthesis beckons policymakers to weave together tax rates and precision-targeted redistribution, crafting tax systems that wield the potential for tangible and substantial reductions in economic disparity.

physics.soc-ph↗

arXiv2023

Wealth distribution on a dynamic complex network

We present an agent-based model of microscopic wealth exchange in a dynamic network to study the topological features associated with economic inequality. The model evolves through two alternating processes, the conservative exchange of wealth between connected agents and the rewiring of connections, which depends on the wealth of the agents. The two dynamics are interrelated; from the dynamics of wealth a complex network emerges and the network in turn dictates who interacts with whom. We study the time evolution and the economic and topological asymptotic characteristics of the model for different values of a social protection factor $f$, which favors the poorest agent in each wealth transaction. In the case of $f=0$, our results show condensation of wealth and connections in a few agents, in accordance with the mean field models with respect to wealth. Low values of $f$ favor agents from the middle and upper classes, leading to the formation of hubs in the network. As $f$ increases, the network restriction on exchanges gives rise to an egalitarian society different from the results outside the midfield network.

physics.soc-ph↗

arXiv2022

Equal opportunities lead to maximum wealth inequality

If wealthier people have advantages in having higher returns than poor, inequality will unequivocally increase, but is equal opportunity enough to prevent it? According to several models in economics and econophysics, no. They all display wealth concentration as a peculiar feature of its dynamics, even though no individual can have repeating gains advantage. Here, generalizing these particular models, we present a rigorous analytical demonstration, using master equation formalism, that any fair market that gives each agent the same expected return conducts the system to maximum inequality.

cond-mat.stat-mech↗

arXiv2020

Wealth concentration in systems with unbiased binary exchanges

Aiming to describe the wealth distribution evolution, several models consider an ensemble of interacting economic agents that exchange wealth in binary fashion. Intriguingly, models that consider an unbiased market, that gives to each agent the same chances to win in the game, are always out of equilibrium until the perfect inequality of the final state is attained. Here we present a rigorous analytical demonstration that any system driven by unbiased binary exchanges are doomed to drive the system to perfect inequality and zero mobility.

q-fin.GN↗

arXiv2020

Urban Scaling of COVID-19 epidemics

Susceptible-Invective-Recovered (SIR) mathematical models are in high demand due to the COVID-19 pandemic. They are used in their standard formulation, or through the many variants, trying to fit and hopefully predict the number of new cases for the next days or weeks, in any place, city, or country. Such is key knowledge for the authorities to prepare for the health systems demand or to apply restrictions to slow down the infectives curve. Even when the model can be easily solved ---by the use of specialized software or by programming the numerical solution of the differential equations that represent the model---, the prediction is a non-easy task, because the behavioral change of people is reflected in a continuous change of the parameters. A relevant question is what we can use of one city to another; if what happened in Madrid could have been applied to New York and then, if what we have learned from this city would be of use for São Paulo. With this idea in mind, we present an analysis of a spreading-rate related measure of COVID-19 as a function of population density and population size for all US counties, as long as for Brazilian cities and German cities. Contrary to what is the common hypothesis in epidemics modeling, we observe a higher {\em per-capita} contact rate for higher city's population density and population size. Also, we find that the population size has a more explanatory effect than the population density. A contact rate scaling theory is proposed to explain the results.

q-bio.PE↗

arXiv2020

Inequality, a scourge of the XXI century

Social and economic inequality is a plague of the XXI Century. It is continuously widening, as the wealth of a relatively small group increases and, therefore, the rest of the world shares a shrinking fraction of resources. This situation has been predicted and denounced by economists and econophysicists. The latter ones have widely used models of market dynamics which consider that wealth distribution is the result of wealth exchanges among economic agents. A simple analogy relates the wealth in a society with the kinetic energy of the molecules in a gas, and the trade between agents to the energy exchange between the molecules during collisions. However, while in physical systems, thanks to the equipartition of energy, the gas eventually arrives at an equilibrium state, in many exchange models the economic system never equilibrates. Instead, it moves toward a "condensed" state, where one or a few agents concentrate all the wealth of the society and the rest of agents shares zero or a very small fraction of the total wealth. Here we discuss two ways of avoiding the "condensed" state. On one hand, we consider a regulatory policy that favors the poorest agent in the exchanges, thus increasing the probability that the wealth goes from the richest to the poorest agent. On the other hand, we study a tax system and its effects on wealth distribution. We compare the redistribution processes and conclude that complete control of the inequalities can be attained with simple regulations or interventions.

q-fin.GN↗

arXiv2019

Wealth Distribution Models with Regulations: Dynamics and Equilibria

Simple agent based exchange models are a commonplace in the study of wealth distribution in an artificial economy. Generally, in a system that is composed of many agents characterized by their wealth and risk-aversion factor, two agents are selected sequentially and randomly to exchange wealth, allowing for its redistribution. Here we analyze how the effect of a social protection policy, which favors agents of lower wealth during the exchange, influences stability and some relevant economic indicators of the system. On the other hand, we study how periods of interruption of these policies produce, in the short and long term, changes in the system. In most cases, a steady state is reached, but with varying relaxation times. We conclude that regulations may improve economic mobility and reduce inequality. Moreover, our results indicate that the removal of social protection entails a high cost associated with the hysteresis of the distribution of wealth. Economic inequalities increase during a period without social protection, but also they remain high for an even longer time and, in some extreme cases, inequality may be irreversible, indicating that the withdrawal of social protection yields a high cost associated with the hysteresis of the distribution of wealth.

cond-mat.stat-mech↗

arXiv2018

Tomlinson model improved with no ad-hoc dissipation

The origin of friction force is a very old problem in physics, which goes back to Leonardo da Vinci or even older times. Extremely important from a practical point of view, but with no satisfactory explanation yet. Many models have been used to study dry sliding friction. The model introduced in the present work consists in one atom that slide over a surface represented by a periodic arrangement of atoms, each confined by an independent harmonic potential. The novelty of our contribution resides in that we do not include an {\em ad hoc} dissipation term as all previous works have done. Despite the apparent simplicity of the model it can not be solved analytically, so the study is performed solving the Newton's equations numerically. The results obtained so far with the present model are in accordance with the Tomlinson model, often used to represent the atomic force microscope. The atomic-scale analysis of the interaction between sliding surfaces is necessary to understand the non-conservative lateral forces and the mechanism of energy dissipation which can be thought as effective emerging friction.

cond-mat.mes-hall↗

arXiv2018

Empirical determination of the optimum attack for fragmentation of modular networks

All possible removals of $n=5$ nodes from networks of size $N=100$ are performed in order to find the optimal set of nodes which fragments the original network into the smallest largest connected component. The resulting attacks are ordered according to the size of the largest connected component and compared with the state of the art methods of network attacks. We chose attacks of size $5$ on relative small networks of size $100$ because the number of all possible attacks, ${100}\choose{5}$ $\approx 10^8$, is at the verge of the possible to compute with the available standard computers. Besides, we applied the procedure in a series of networks with controlled and varied modularity, comparing the resulting statistics with the effect of removing the same amount of vertices, according to the known most efficient disruption strategies, i.e., High Betweenness Adaptive attack (HBA), Collective Index attack (CI), and Modular Based Attack (MBA). Results show that modularity has an inverse relation with robustness, with $Q_c \approx 0.7$ being the critical value. For modularities lower than $Q_c$, all heuristic method gives mostly the same results than with random attacks, while for bigger $Q$, networks are less robust and highly vulnerable to malicious attacks.

physics.soc-ph↗

arXiv2018

Sliding and dry friction: Prandtl-Tomlinson athermal model revisited

The microscopic origin of friction has been the goal of several theoretical studies in the last decades. Depending on the investigated systems or models, on the simulation techniques or conditions, different and somewhat contradictory results have been found, even when using the same model. In this contribution, we address this apparent paradox in a well-known case, the Prandtl-Tomlinson model at zero temperature, studying the force-velocity relation for a wide range of velocities not previously presented. Including much more data density for the non trivial regions, we are able to shed light on this problem and at the same time, provide new insight in the use of the paradigmatic Tomlinson model for the secular problem of friction laws.

cond-mat.mes-hall↗

arXiv2016

Performance of attack strategies on modular networks

Vulnerabilities of complex networks have became a trend topic in complex systems recently due to its real world applications. Most real networks tend to be very fragile to high betweenness adaptive attacks. However, recent contributions have shown the importance of interconnected nodes in the integrity of networks and module-based attacks have appeared promising when compared to traditional malicious non-adaptive attacks. In the present work we deeply explore the trade-off associated with attack procedures, introducing a generalized robustness measure and presenting an attack performance index that takes into account both robustness of the network against the attack and the run-time needed to obtained the list of targeted nodes for the attack. Besides, we introduce the concept of deactivation point aimed to mark the point at which the network stops to function properly. We then show empirically that non-adaptive module-based attacks perform better than high degree and betweenness adaptive attacks in networks with well defined community structures and consequent high modularity.

physics.soc-ph↗

arXiv2015

Complex networks vulnerability to module-based attacks

In the multidisciplinary field of Network Science, optimization of procedures for efficiently breaking complex networks is attracting much attention from practical points of view. In this contribution we present a module-based method to efficiently break complex networks. The procedure first identifies the communities in which the network can be represented, then it deletes the nodes (edges) that connect different modules by its order in the betweenness centrality ranking list. We illustrate the method by applying it to various well known examples of social, infrastructure, and biological networks. We show that the proposed method always outperforms vertex (edge) attacks which are based on the ranking of node (edge) degree or centrality, with a huge gain in efficiency for some examples. Remarkably, for the US power grid, the present method breaks the original network of 4941 nodes to many fragments smaller than 197 nodes (4% of the original size) by removing mere 164 nodes (~3%) identified by the procedure. By comparison, any degree or centrality based procedure, deleting the same amount of nodes, removes only 22% of the original network, i.e. more than 3800 nodes continue to be connected after that

physics.soc-ph↗