Estimation of the Gini coefficient using the method of simultaneous equations with quintile data

The simultaneous equation method proposed in this paper uses quintile data to estimate the Gini coefficient. Using Schader and Schmid’s four-parameter Lorenz curve and a dataset of sixteen economies from the World Income Inequality Database (WIID), the proposed method is significantly superior to the error minimization technique in estimating the Gini coefficient with quintile data. In the case of large samples, based on the randomly generated quintile data of Beta-2 and Lognormal income distribution, the proposed method not only obtains an accurate estimate of the Gini coefficient, but also performs well in fitting decile income shares. Compared to the error minimization technique, the advantages of the simultaneous equations method in estimating the Gini coefficient using the records of Poverty and Inequality Platform (PIP) and Luxembourg Income Study (LIS) in WIID have also been validated.