Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userStudy of a model for the distribution of wealth
100
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
An equation for the evolution of the distribution of wealth in a population of economic agents making binary transactions with a constant total amount of money has recently been proposed by one of us (RLR). This equation takes the form of an iterated nonlinear map of the distribution of wealth. The equilibrium distribution is known and takes a rather simple form. If this distribution is such that, at some time, the higher momenta of the distribution exist, one can find exactly their law of evolution. A seemingly simple extension of the laws of exchange yields also explicit iteration formulae for the higher momenta, but with a major difference with the original iteration because high order momenta grow indefinitely. This provides a quantitative model where the spreading of wealth, namely the difference between the rich and the poor, tends to increase with time.
rate research
Read More
We investigate the wealth evolution in a system of agents that exchange wealth through a disordered network in presence of an additive stochastic Gaussian noise. We show that the resulting wealth distribution is shaped by the degree distribution of the underlying network and in particular we verify that scale free networks generate distributions with power-law tails in the high-income region. Numerical simulations of wealth exchanges performed on two different kind of networks show the inner relation between the wealth distribution and the network properties and confirm the agreement with a self-consistent solution. We show that empirical data for the income distribution in Australia are qualitatively well described by our theoretical predictions.
A money-based model for the power law distribution (PLD) of wealth in an economically interacting population is introduced. The basic feature of our model is concentrating on the capital movements and avoiding the complexity of micro behaviors of individuals. It is proposed as an extension of the Equiluz and Zimmermanns (EZ) model for crowding and information transmission in financial markets. Still, we must emphasize that in EZ model the PLD without exponential correction is obtained only for a particular parameter, while our pattern will give it within a wide range. The Zipf exponent depends on the parameters in a nontrivial way and is exactly calculated in this paper.
In this paper we address the question of the size distribution of firms. To this aim, we use the Bloomberg database comprising multinational firms within the years 1995-2003, and analyze the data of the sales and the total assets of the separate financial statement of the Japanese and the US companies, and make a comparison of the size distributions between the Japanese companies and the US companies. We find that (i) the size distribution of the US firms is approximately log-normal, in agreement with Gibrats observation (Gibrat 1931), and in contrast (ii) the size distribution of the Japanese firms is clearly not log-normal, and the upper tail of the size distribution follows the Pareto law. It agree with the predictions of the Simon model (Simon 1955). Key words: the size distribution of firms, the Gibrats law, and the Pareto law
Complex networks provide us a new view for investigation of immune systems. In this paper we collect data through STRING database and present a model with cooperation network theory. The cytokine-protein network model we consider is constituted by two kinds of nodes, one is immune cytokine types which can act as acts, other one is protein type which can act as actors. From act degree distribution that can be well described by typical SPL -shifted power law functions, we find that HRAS.TNFRSF13C.S100A8.S100A1.MAPK8.S100A7.LIF.CCL4.CXCL13 are highly collaborated with other proteins. It reveals that these mediators are important in cytokine-protein network to regulate immune activity. Dyad act degree distribution is another important property to generalized collaboration network. Dyad is two proteins and they appear in one cytokine collaboration relationship. The dyad act degree distribution can be well described by typical SPL functions. The length of the average shortest path is 1.29. These results show that this model could describe the cytokine-protein collaboration preferably
Both theoretical and applied economics have a great deal to say about many aspects of the firm, but the literature on the extinctions, or demises, of firms is very sparse. We use a publicly available data base covering some 6 million firms in the US and show that the underlying statistical distribution which characterises the frequency of firm demises - the disappearances of firms as autonomous entities - is closely approximated by a power law. The exponent of the power law is, intriguingly, close to that reported in the literature on the extinction of biological species.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
