Wealth and Income Distribution : A Review Towards New Trends (original) (raw)
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The Distribution of Income and Wealth
New Economic Windows, 2016
In recent years, after a long period of decline, inequality in the distribution of income and wealth has increased. In the major OECD countries the Gini index went from 0.30 to 0.35; 0.1 % of the super-rich in the US in 2013 have 22 % of the country's wealth (note that from 1946 to 1988 the share was less than 10 %). To have similar levels one must go back to the years of the Great Depression. The interest in income and wealth distribution is exemplified by the recent works of Stiglitz (2012, 2015a), Piketty (2014), and Atkinson (2015). It seems to have two separate causes: slow growth and its unsustainability. The first element is almost trivial: when the cake is growing a lot, one can legitimately worry less about its distribution. Conversely, now that millions of Europeans are at risk of poverty the problem of distribution arises strongly. And even more so when one considers global development, since it is incompatible with the current mode of production and consumption. Redistribution becomes a necessity. The economic crisis has translated, also, into a crisis of economic theory. In particular, the hypothesis of micro-founded equilibrium (i.e., based on methodological individualism) and the absence of interaction between heterogeneous agents, which as we will see are the determinants of the distribution, imposes a straightjacket on the mainstream box of tools which inhibits it from any application on distribution. The interaction among agents can be identified with the causa causans of the nonlinearity that originates the distribution as an emergent phenomenon. The laws of thermodynamics, among the most certain laws we have in physics, are the result of chance: random behavior determined by the interaction of billions of billions of molecules resulting in macroscopic regularity. This is what happens to the distribution of income and wealth, but in economics molecules are atoms in society and their dimensions are heterogeneous, so that there is the effect of St. Matthew (Mt 13:12): "Whoever has will be given more, and they will have an vii
A model of distribution of the wealth in a society based on the properties of complex networks has been proposed. The wealth is interpreted as a consequence of communication possibilities and proportional to the number of connections possessed by a person (as a vertex of the social network). Numerical simulation of wealth distribution shows a transition from the Pareto law to distribution with a gap demonstrating the absence of the middle class. Such a transition has been described as a second-order phase transition, the order parameter has been introduced and the value of the critical exponent has been found.
From Galileo to Modern Economics
Wealth Distribution This chapter begins with Michal Kalecki's witty epigram, quoted by Josef Steindl (1965, p. 18): "Economics consists of theoretical laws which nobody has verified and empirical laws which nobody can explain." Never more than in the case of the empirical Pareto law has Kalecki's witticism seemed so appropriate. Whether Pareto law is understandable or not, econophysicists consider the Pareto curve one of the forerunners of econophysics. The invariant distribution of income over time and space was clearly an economic phenomenon that economists were unable to account for or predict. Physicists were able to offer a different interpretation of the Pareto curve, based on appropriate methods and approaches, that contained it within the broader analysis of complex systems (see Richmond et al. 2013, p. 16 ff.). Pareto law is introduced here as a stage in the journey toward econophysics. Its empirical features generated different interpretations, and now that it is largely a matter for the econophysicists many issues remain concerning its stability and universality, the mobility among different classes of income, and so on. Pareto did not really try to explain his law from an economic perspective. As he confirmed in his Trattato di sociologia (1916) (The Mind and
Properties of wealth distribution in multi-agent systems of a complex network
2008
We present a simple model for examining the wealth distribution with agents playing evolutionary games (the Prisoners' Dilemma and the Snowdrift Game) on complex networks. Pareto's power law distribution of wealth (from 1897) is reproduced on a scalefree network, and the Gibbs or log-normal distribution for a low income population is reproduced on a random graph. The Pareto exponents of a scale-free network are in agreement with empirical observations. The Gini coefficient of an ER random graph shows a sudden increment with game parameters. We suggest that the social network of a high income group is scale-free, whereas it is more like a random graph for a low income group.
The Distribution of Wealth: Measurement and Models
Journal of Economic Surveys, 1990
Analysts debating the consequences of a policy change for the wealth distribution may come to different conclusions because of different views about how the distribution should be defined and measured, or about the processes determining the distribution. The aim of this survey is to provide an analytical framework within which such conflicts may be assessed. The first part of the paper discusses conceptual issues in the definition of 'wealth', and compares methods of deriving estimates of wealth distribution. The second, and larger, part of the paper surveys lifecycle and intergenerational models of the distribution of wealth, including a discussion of the role played by inheritance. The presentation is largely theoretical. Indeed, one of the paper's conclusions is that empirical modelling of the wealth distribution is underdeveloped , at least for the purposes of addressing many topical policy issues.
A family-network model for wealth distribution in societies
Physica A-statistical Mechanics and Its Applications, 2005
A model based on first-degree family relations network is used to describe the wealth distribution in societies. The network structure is not a priori introduced in the model, it is generated in parallel with the wealth values through simple and realistic dynamical rules. The model has two main parameters, governing the wealth exchange in the network. Choosing their values realistically, leads to wealth distributions in good agreement with measured data. The cumulative wealth distribution function has an exponential behavior in the low and medium wealth limit, and shows the Pareto-like power-law tail for the upper 5% of the society. The obtained Pareto indexes are in good agreement with the measured ones. The generated family networks also converge to a statistically stable topology with a simple Poissonian degree distribution. On this family network many interesting correlations are studied, and the main factors leading to wealth diversification and the formation of the Pareto law are identified. r
Wealth distribution on a dynamic complex network
arXiv (Cornell University), 2023
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.
A Nontechnical Analysis of the Distribution of Income
1974
A Nontechnical Analysis of the Distribution of Income Designed to make the fruits of my research effort intelligible to the nonspecialist, this chapter presents an elementary analysis of the determinants of the distribution of labor market income. Within this framework it also discusses some of the more important aspects of the theory and findings comprising the technical chapters in Parts B and C. EQUALIZING WAGE DIFFERENTIALS AND NONMONEY ASPECTS OF JOBS No discussion of the theory of labor market income can ignore Adam Smith's contribution. In his 1776 volume, The Wealth of Nations, Smith introduced the idea of compensating wage differentials in competitive labor markets.' He wrote: "The whole of the advantages and disadvantages of the different employments of labor and stock must, in the same neighborhood, be either perfectly equal or constantly tending to equality. If in the same neigh. borhood there was any employment evidently either more or less advantageous than the rest, so many people would crowd into it in the one case, and so many would desert it in the other, that its 1. Modern Library edition, Book I, Chapter 10, p. 99. 1 am willing to wager that Smith's Chapter 10 is the most frequently cited work written prior to 1960 on reading lists in labor economics.
An agent-based model of the observed distribution of wealth in the United States
Journal of Economic Interaction and Coordination, 2017
Pareto cautiously asserted that the wealth and income distributions which bear his name are universal, basing his argument on observations of this distribution in many different types of economies. In this paper, we present an agent based model (and a scalable approximation of it) in a closely related spirit. The central feature of this model is that wealth enables an individual to secure more wealth. Specifically, the important and novel feature of this model is its ability to simultaneously produce both the Pareto distribution observed in empirical data for the top 10% of the population and the exponential distribution observed for the lower 90%. We show that the model produces these distributions of wealth when initialized with an equitable distribution.