PANEL DATA ANALYSIS MAKING EFFECT THE VARIABLES ON INCOME DISTRIBUTION INJUSTICE
PANEL DATA ANALYSIS MAKING EFFECT THE VARIABLES ON INCOME DISTRIBUTION INJUSTICE

Summary/Abstract: Income distribution injustice is one of the serious and complex problems in development of a country. In a country, for economic development to spread over social basis, it is necessary for the gains engendered by growth to be shared with all society. Thanks to this, a country also provides economic growth as well as welfare increase. Spread of economic growth over social basis is closely related to a fair income distribution. In the study carried out, income distribution injustice is associated with Gini Coefficient. While that Gini Coefficient approaches zero means that country incomes are fairly distributed to every sector of society, that it approaches to one expresses that incomes are collected in certain sectors and that income justice in that country becomes worse. In this study, utilizing the1990-2020 annual data of the countries such as USA, Brazil, Canada, Finland and United Kingdom, it was aimed to identify that income distribution injustice are affected from which of the variables such as employment rate, per capita income, fertility rate, urbanization and investment rate and how. As dependent variable of the study, Gini Coefficient was used. In the study, utilized panel data analysis, according to the results of long term PDOLS predictor analysis, it was concluded that an increase of one unit occurring in per capita income, gross capital formation (investment) and employment rate affected Gini Coefficient in positive direction, that fertility rate was insignificant, and that urbanization negatively affected it.

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