The
Gini coefficient which measures the unfair distribution of income is a value
between 0 and 1. As the index value approaches to 1, unfairness increases and
as it approaches to 0, income distribution becomes fairer. The aim of this
study is to examine the effect of real interest on income distribution in 5
developing countries which are close to each other in terms of real per capita
income with panel data analysis. In this context, since the data of 2000-2016
include cross sectional dependency, second generation panel root tests were
used. Since the series are stable on different levels, ARDL model was utilized.
Then, the coefficient between the variables were determined by using the PMG
estimator and causality analysis was conducted. According to the result of the
study, although there isn’t a short-term relationship between the variables,
there is a cointegrated relationship in long-term. Furthermore, according to
the PMG estimator, an increase of 1 unit, increases the Gini coefficient by
0.007. Since the conducted causality analysis was resulted in accordance with
the Gini coefficient from real interests, it verifies this result. Since the
increase in real interests increases the Gini coefficient, real interests
should be decreased for a more fair income distribution, according to the
result of this study.
Primary Language | English |
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Subjects | Economics |
Journal Section | Articles |
Authors | |
Publication Date | March 31, 2019 |
Published in Issue | Year 2019 |