The velocity of money in a life-cycle model

Wang, Yougui; Qiu, Hanqing

doi:10.1016/j.physa.2005.01.053

Cited by 6 publications

(4 citation statements)

References 27 publications

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“…Other studies calculated the holding time [66] of money, which indicated in turn the mobility of the money in a model under a given dynamics. Another similar study [67] calculated the velocity of money in a life-cycle model. Studies of gas-like or particle-exchange models have already been carried out on complex networks [68,69].…”

Section: Other Model Studiesmentioning

confidence: 99%

Kinetic exchange models for income and wealth distributions

2007

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Abstract. Increasingly, a huge amount of statistics have been gathered which clearly indicates that income and wealth distributions in various countries or societies follow a robust pattern, close to the Gibbs distribution of energy in an ideal gas in equilibrium. However, it also deviates in the low income and more significantly for the high income ranges. Application of physics models provides illuminating ideas and understanding, complementing the observations.

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Section: Other Model Studiesmentioning

confidence: 99%

Kinetic exchange models for income and wealth distributions

2007

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“…Therefore, models that have been proposed, necessarily select a subset of factors considered important for the phenomena to be described. For instance, there are studies of income and wealth distribution [3,4], using gas like models [5], life-cycle models [6],…”

Section: Introductionmentioning

confidence: 99%

Modelling Trading Networks and the Role of Trust

Barrio,

Govezensky,

Ruiz-Gutiérrez

et al. 2016

Preprint

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We present a simple dynamical model for describing trading interactions between agents in a social network by considering only two dynamical variables, namely money and goods or services, that are assumed conserved over the whole time span of the agents' trading transactions. A key feature of the model is that agent-to-agent transactions are governed by the price in units of money per goods, which is dynamically changing, and by a trust variable, which is related to the trading history of each agent. All agents are able to sell or buy, and the decision to do either has to do with the level of trust the buyer has in the seller, the price of the goods and the amount of money and goods at the disposal of the buyer. Here we show the results of extensive numerical calculations under various initial conditions in a random network of agents and compare the results with the available related data. In most cases the agreement between the model results and real data turns out to be fairly good, which allow us to draw some general conclusions as how different trading strategies could affect the distribution of wealth in different kinds of societies.

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“…These works can be divided into two parts. One is about how the money moves in the assumed economy [20,21,22]. As we know, the money is not static even after the money distribution gets steady.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Process of Money Transfer Models

Wang

Ding

2005

New Economic Windows

Self Cite

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We have studied numerically the statistical mechanics of the dynamic phenomena, including money circulation and economic mobility, in some transfer models. The models on which our investigations were performed are the basic model proposed by A. Drȃgulescu and V. Yakovenko [1], the model with uniform saving rate developed by A. Chakraborti and B.K. Chakrabarti [2], and its extended model with diverse saving rate [3]. The velocity of circulation is found to be inversely related with the average holding time of money. In order to check the nature of money transferring process in these models, we demonstrated the probability distributions of holding time. In the model with uniform saving rate, the distribution obeys exponential law, which indicates money transfer here is a kind of Poisson process. But when the saving rate is set diversely, the holding time distribution follows a power law. The velocity can also be deduced from a typical individual's optimal choice. In this way, an approach for building the micro-foundation of velocity is provided. In order to expose the dynamic mechanism behind the distribution in microscope, we examined the mobility by collecting the time series of agents' rank and measured it by employing an index raised by economists. In the model with uniform saving rate, the higher saving rate, the slower agents moves in the economy. Meanwhile, all of the agents have the same chance to be the rich. However, it is not the case in the model with diverse saving rate, where the assumed economy falls into stratification. The volatility distribution of the agents' ranks are also demonstrated to distinguish the differences among these models.

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The velocity of money in a life-cycle model

Cited by 6 publications

References 27 publications

Kinetic exchange models for income and wealth distributions

Kinetic exchange models for income and wealth distributions

Modelling Trading Networks and the Role of Trust

Dynamic Process of Money Transfer Models

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