Financial Inclusion on Income Inequality

Abstract

Income inequality means a great difference of income deliveries with a high attentiveness of income generally in the hands of a small numbers of people. Financial inclusion is that the accessibility of persons and trades to beneficial and reasonable financial products and services to meet their needs to deliver in an accountable and durable way. A number of investigational studies have exasperated to clarify income inequality or distribution from numerous stances. Mainly some studies, those based on time series data, are often pre-occupied with shaping the special effects of designated macroeconomic variables say, inflation and unemployment level on income distribution, say. (Tarantelli 1986) and (Farré and Vella 2008), though another time-series studies observes the special effects of fiscal policy, specially tax rate, on inequality, say. (Cevik and Correa-Caro 2019) and (Saez 2004). The Unit Root Test (shown in table: 1, 2 & 3) has been conducted of 6 tests i.e., Levin, Lin & Chu t*,Im, Pesaran and Shin W-stat, ADF - Fisher Chi-square, PP- Fisher Chi-square, Breitung t-stat and Hadri Z-stat Here, GINI is dependent variable, Financial Inclusion are ATM, BCD, and DCB, and rest of them are control variable and tests are held on at level (Y) and first difference (ΔY). The Co-integration test (shown in Table: 4,5,& 6) has been conducted with 2 tests i.e., Pedroni test and Kao Test under 11 segments i.e., v-Statistic, rho-Statistic, PP-Statistic ADF-Statistic, v-Statistic_w, rho-Statistic_w, PP-Statistic_w, ADF-Statistic_w, Group rho-Statistic, Group PP-Statistic, Group ADF-Statistic for 3 models, say, ATM, BCD, and DCB. Cross sectional dependency test shown in table 7, and in Baseline model estimation (Regression analysis – OLS) (shown in table: 8, 9 and 10), has been conducted based on OLS and Fixed Effect. GMM and Sys-GMM Test conducted by using 3 steps like model [1], [2] , and [3] ( shown in table 11, 12, and 13), and causality test shown in table 14,15,and 15 for LIC, LMIC and all. By conducting in the Unit Root Test has been found that majority of the values become stationery after first difference. Besides this, the Co-integration test (shown in Table: 4) with 2 tests say, in Pedroni test, when we consider ATM as financial inclusion, there is no co-integration. Similarly, there are 3 outcome in BCD and 2 outcome in DCB are significant respectively that means there is no long-run relationship among 3 models in pedroni test, however, in Kao test, majority of outcome are significant which implies the long-run relationship, Furthermore, in conducting in Baseline model estimation, FI has positive impact while considering BCD and DCB as a FI, both has positive impact on income inequality though it is nominal. In GMM test, impact positively on Financial Inclusion but Remittance has negative influence, and in Sys-GMM explain that both BCD, Money, and DCP has positive impact, while DCF impact inversely on Income Inequity and in Causality test exposed that easy access to financial services for the unbanked population the country will be affected on income inequality and a good relationship between financial inclusion and income inequality for overall countries at level for LIC, LMIC, and All respectively. The literature has been identified as the relationship between financial inclusion and income inequality I observed in LIC (Lower Income Countries), LMIC (lower Middle Income Countries), and all countries. Here, notable thing is that there are so many factors which impacts on income forcing helps to reduce inequality from the society in the empirical model of the economy. I found that the level of human development by employing financial services regardless it reduces or increments inequality through ATM, DCB, BCD , FDI, M (Money), and Y and sometimes engaged in Mobile Banking services (to transfer money from one place to another) who are unbanked population in the country. Most of the time I observed by involving financial inclusion specifically I mention say, south Asian countries, Sub-Saharan Africa, developing countries and some developed countries have influence positively by reshuffling education system to engage large population regarding improve life-style and reduction disparity from the society in some cases.