Applying of Fuzzy Nonlinear Regression to Investigate the Effect of Information and Communication Technology (ICT) on Income Distribution

Reza Ashraf Ganjoei,Hossein Akbarifard,Sayyed Abdol Majid Jalaee Esfandabadi,Mashaallah Mashinchi,Anna M Gil-Lafuente

doi:10.1155/2021/5545213

Abstract

The main focus of this paper is to extend fuzzy regression and its application. Therefore, we used nonlinear modeling to investigate the impact of information and communication technology (ICT) on the Gini coefficient. Hence, we calculated the three borders upside, medium, and downside of the Gini coefficient. We found no evidence of reduced income inequality when decreasing the use of ICT goods. However, with the increased use of ICTs, income inequality decreases over time. Also, the results showed that the effect of ICT commodities on the Gini coefficient was the inverted U situation. Understanding this impact is very important from the perspective of planning and building infrastructure for poverty reduction.

Highlights

Gini coefficient is used to examine the distribution of income in society. e Gini coefficient which was developed by Gini [5] can be used, so that graphically, the density ratio of various species could be placed against density ratio of each individual or each species. e Gini coefficient is a statistical dispersion measurement index that is usually used to measure inequality in the income or wealth distribution in a statistical population [5]
In the FLSTAR model, the appropriate transfer function and variable are selected according to the studied variables, which can be used to calculate income inequality in proportion using of information and communication technology (ICT) goods. erefore, the FLSTAR model has extraordinary flexibility and analysis in accordance with economic conditions compared with classical regression (CR) methods
0.320 0.383 0.399 0.400 0.375 0.358 0.368 0.362 0.371 0.388 0.384 0.401 0.400 0.402 0.322 0.360 0.370 0.363 0.364 0.376 0.382 0.399 0.434 0.419 0.424 income inequality was investigated from an international perspective during the period 2001–2014. e results suggested that the effect of ICT on income inequality depended both on the specific type of ICT and the measure of income inequality

Summary

Consequences of increasing inequality

Channels that are affected (i) High-skill biased technological mutation (i) Economies of scale (ii) Automation and (e.g., additive robotics manufacturing). Methodology of the Research e advantage of this study is that it provides a method for analyzing the impact of ICT goods on income inequality borders For this purpose, the nonlinear behavior of economic variables has been investigated using the fuzzy rulebased system (FRBS) and the nonlinear LSTAR model. E final step of modeling the nonlinear behavior of the variables is done using equation (15) In this stage, we can calculate the effect of ICT goods on the Gini coefficient in the upside, medium, and downside bands using a fuzzy inference system. The effect of ICT goods on income inequality (Gini coefficient borders) is calculated using nonlinear modeling as in (15) and fuzzy inference system [34]. According to the impact of ICT goods on income inequality, the borders upside, medium, and downside are calculated so that in the downside

Fuzzy logistic smooth transition autoregressive

Borders Upside Medium

Year Gini coefficient Down Medium Upside

Down border Medium border Upside border