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Zahra Huseynova: The Correlation Between Gender Pay GAP AND GDP Growth In Azerbaijan Economy

                    In the paper, we also used some control independent variable for against bias or other
                    problems. The first control variable is literacy ratio of males to females. This number
                    is acquired by dividing one variable to another. First is primary school completion
                    rate for males as percentage of male population in given year and the second is female
                    primary school completion rate as percentage of total female population. The data is
                    obtained from The State Statistical Committee of the Republic of Azerbaijan, MDG
                    indicators of the Republic of Azerbaijan.

                    The last variable Gini Index for Azerbaijan. Gini coefficient is discovered by Italian
                    statistician Corrado Gini in 1912. The index is used to measure income distribution in
                    the given society so, the number shows inequality rate in the country. The graphical
                    representation of coefficient is demonstrated by the help of Lorenz curve where flatter
                    curve means more inequality. The coefficient varies among 0 and 100% or 0 and 1.
                    While  0  presents  perfect  equality,  1  shows  perfect  inequality  so,  high  coefficient
                    means high inequal distribution of income (Westfall, 2020). In our analysis, we get
                    Gini  Coefficient  from  Trading  Economics  which  also  refer  to  World  Bank
                    estimations. However, our data regarding Gini coefficient suffers from missing data
                    which might affect the results.

                    Additionally, for our main variables we added literacy rate gap for adult population to
                    look correlation between wage gap and them separately, which again is provided by
                    World Bank's World Development Indicators database.

                    METHODOLOGY
                    For the regression analysis we referred to the methodology conducted by Sherri Haas
                    (2006)  but  with  some  modifications.  The  regression  equation  and  explanation  of
                    variable are given below:

                       wage = β0 + β1 lgdp + β2 literacy + β3 gini + β4 year + u

                    Table 3: Explanation of variables
                     Variables         Explanation
                     wage              wage ratio of male and female workers
                     year              1991-2020
                     literacy          literacy rate of male to female population
                     lgdp              logarithm of real GDP per capita
                     gini              gini (inequality)coefficient
                    Source: The author







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