On the Analysis of the Efficiency of a Piecewise-Linear Model for Progressive Taxation

2020 ◽  
Vol 27 (6) ◽  
pp. 79-85
Author(s):  
V. S. Mkhitaryan ◽  
V. F. Shishov ◽  
D. V. Iskorkin

The article presents the authors’ ideas regarding the measurement of the effectiveness of the proposed modernized version of the progressive taxation scale. The comparative statistical and economic analysis of taxation of individuals carried out in the article showed that in most countries with developed market economies, a progressive taxation scale is used, which allows taking into account population ability to pay and the established subsistence minimum. At present, Russia is practically one of the developed countries in which a flat scale has remained. But recently, in our country, measures are being taken to introduce some elements of progressive taxation. The paper also shows that a significant drawback of the progressive scale used in different countries is the abrupt change in the size of the tax. It is proposed that, the so-called «piecewise-linear» model of the progressive taxation scale that from the taxpayer’s perspective is fairer, be used. Using statistical data, the authors demonstrated the advantages of the proposed «piece-wise-linear» model of the progressive taxation scale in comparison with the «flat» scale. The «piecewise linear» scale proposed in the study will allow individuals (taxpayers) to make an easier transition to a progressive tax rate. To assess the effectiveness of the proposed version of the «piecewise-linear» taxation scale, an economic and mathematical model has been developed, which implies tax exemption for persons with incomes below the subsistence level and an increase in the tax rate, compared to the existing one, for persons with large incomes. The model was tested on data of Rosstat on the income of individuals. The introduction of «piecewise-linear» taxation scale will, in authors’ opinion, increase tax collection and more fully implement the distribution function of taxation, which will ultimately stimulate the development of the economy and social sphere.

2020 ◽  
Vol 102 (3) ◽  
Author(s):  
Tomoshige Miyaguchi ◽  
Takamasa Miki ◽  
Ryota Hamada

2018 ◽  
Vol 2018 ◽  
pp. 1-16
Author(s):  
Weiying Meng ◽  
Liyang Xie ◽  
Yu Zhang ◽  
Yawen Wang ◽  
Xiaofang Sun ◽  
...  

This paper presents a study on the fatigue life prediction of notched fiber-reinforced 2060 Al-Li alloy laminates under spectrum loading by applying the constant life diagram. Firstly, a review on the state of the art of constant life diagram models for the life prediction of composite materials is given, which highlights the effect on the forecast accuracy. Then, the fatigue life of notched fiber-reinforced Al-Li alloy laminates (2/1 laminates and 3/2 laminates) is tested under cyclic stress, which has different stress cycle characteristics (constant amplitude loading and Mini-Twist spectrum loading). The introduced models are successfully realized based on the available experimental data of examined laminates. In the case of Mini-Twist spectrum loading, the effect of the constant life diagram on the life prediction accuracy of examined laminates is studied based on the rainflow-counting method and Miner damage criteria. The results show that the simple Goodman model and piecewise linear model have certain advantages compared to other complex models for the life prediction of notched fiber metal laminates with different structures under Mini-Twist loading. From the engineering perspective, the S-N curve prediction based on the piecewise linear model is most applicable and accurate among all the models.


2020 ◽  
Vol 12 (9) ◽  
pp. 1482 ◽  
Author(s):  
Tangao Hu ◽  
Yue Li ◽  
Yao Li ◽  
Yiyue Wu ◽  
Dengrong Zhang

Timely and accurate sea surface wind field (SSWF) information plays an important role in marine environmental monitoring, weather forecasting, and other atmospheric science studies. In this study, a piecewise linear model is proposed to retrieve SSWF information based on the combination of two different satellite sensors (a microwave scatterometer and an infrared scanning radiometer). First, the time series wind speed dataset, extracted from the HY-2A satellite, and the brightness temperature dataset, extracted from the FY-2E satellite, were matched. The piecewise linear regression model with the highest R2 was then selected as the best model to retrieve SSWF information. Finally, experiments were conducted with the Usagi, Fitow, and Nari typhoons in 2013 to evaluate accuracy. The results show that: (1) the piecewise linear model is successfully established for all typhoons with high R2 (greater than 0.61); (2) for all three cases, the root mean square error () and mean bias error (MBE) are smaller than 2.2 m/s and 1.82 m/s, which indicates that it is suitable and reliable for SSWF information retrieval; and (3) it solves the problem of the low temporal resolution of HY-2A data (12 h), and inherits the high temporal resolution of the FY-2E data (0.5 h). It can provide reliable and high temporal SSWF products.


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