Wealth disparities and economic flow: Assessment using an asset exchange model with the surplus stock of the wealthy

How can we limit wealth disparities while stimulating economic flows in sustainable societies? To examine the link between these concepts, we propose an econophysics asset exchange model with the surplus stock of the wealthy. The wealthy are one of the two exchange agents and have more assets than the poor. Our simulation model converts the surplus contribution rate of the wealthy to a new variable parameter alongside the saving rate and introduces the total exchange (flow) and rank correlation coefficient (metabolism) as new evaluation indexes, adding to the Gini index (disparities), thereby assessing both wealth distribution and the relationships among the disparities, flow, and metabolism. We show that these result in a gamma-like wealth distribution, and our model reveals a trade-off between limiting disparities and vitalizing the market. To limit disparities and increase flow and metabolism, we also find the need to restrain savings and use the wealthy surplus stock. This relationship is explicitly expressed in the new equation introduced herein. The insights gained by uncovering the root of disparities may present a persuasive case for investments in social security measures or social businesses involving stock redistribution or sharing

Evaluation of reaction rate of refining agents

To elucidate the thermal decomposition behavior of antimony oxide which is added to promote (re)fming of bubbles in TV glass, an evolved gas analysis (EGA) was conducted using a newly designed device for detecting the gases from the glass batch at increasing temperatures. Furthermore, a mathematical formulation was made to describe the above behavior. From the results of the EGA measurements, three parameters, which govern the reaction rate constant, viz. reaction order, activation energy and frequency factor, were decided. By coupling this mathematical model and the thermal fluid model of glass melts in tank furnaces, it is possible to simulate the conditions of generating refming oxygen in the furnace

Regional Inequality Simulations Based on Asset Exchange Models with Exchange Range and Local Support Bias

To gain insights into the problem of regional inequality, we proposed new regional asset exchange models based on existing kinetic income-exchange models in economic physics. We did this by setting the spatial exchange range and adding bias to asset fraction probability in equivalent exchanges. Simulations of asset distribution and Gini coefficients showed that suppressing regional inequality requires, firstly an increase in the intra-regional economic circulation rate, and secondly the narrowing down of the exchange range (inter-regional economic zone). However, avoiding over-concentration of assets due to repeat exchanges requires adding a third measure; the local support bias (distribution norm). A comprehensive solution incorporating these three measures enabled shifting the asset distribution from over-concentration to exponential distribution and eventually approaching the normal distribution, reducing the Gini coefficient further. Going forward, we will expand these models by setting production capacity based on assets, path dependency on two-dimensional space, bias according to disparity, and verify measures to reduce regional inequality in actual communities.Comment: 14 pages, 8 figures. Published online at http://redfame.com/journal/index.php/aef/article/view/494

Objective Classification of the Sea Level Pressure Distribution Pattern in East Asia: Analysis of the Cold Half of the Year

As the first step in a series of statistical downscaling studies, an objective classification of the sea level pressure (SLP) distribution pattern in the East Asian region was conducted. Patterns classified by this method for the cold half of the year were characterized by referring to their group mean distribution pat terns, prevailing seasons, and those obtained by traditional weather classification methods. On the basis of the time series of patterns obtained, the continuity of each pattern and transition between patterns were also investigated quantitatively depending on the probability. This method is based on multivariate analysis, in which a large number of parameters from the SLP field (distribution pattern) are integrated into a limited number of objective indices, and the distribution patterns are classified depending on the indices. First, SLP data at OOUTC for a period of 30 years (1979-2008) from the NCEP/NCAR dataset were analyzed using principal component analysis (PCA). Then, 10,958 days (distribution patterns) were classified into groups by cluster analysis in the six-dimensional space with the axes of the first six component scores of the PCA. Winter SLP distribution patterns in the East Asian region were classified into 12 groups (patterns). Each pattern was named according to the feature clarified. These patterns were mainly characterized as a strong winter pattern (three groups\u27 Siberian high type, Aleutian low type, mixed type), weak winter pattern (three groups), cyclone pattern, anticyclone/cyclone pattern (two groups), anticyclone pattern (two groups), and others. Our method classified the strong winter pattern into three groups from the meteorological point of view. Through the use of the additionally calculated six-hourly time series of the patterns, the temporal continuity of each group was investigated. The group to which specific groups tend to shift was also clarified quantitatively. In the interannual variation of the frequency of each group, no increasing or decreasing trend was found, especially in those of the strong winter patterns. Our method enables the objective clas sification of the SLP distribution patterns according to the quantitative value. This will be helpful in evaluating climate change quantitatively from the frequency and intensity of each pattern when our method is applied to future SLP distribution patterns in the globally warming world