A New Functional Form For Estimating Lorenz Curves

Abstract

<p class="MsoNormal" style="text-align: justify; margin: 0in 33.3pt 0pt 31.05pt;"><span style="font-size: 10pt; mso-bidi-font-size: 12.0pt;"><span style="font-family: Times New Roman;">The Lorenz curve is a most powerful tool in the analysis of the size distribution of income and wealth. In the past decades, many authors have proposed different functional forms for estimating Lorenz curves from grouped data. Most of the functional forms do not fit the data very well for estimating Lorenz curves. That is why, in this paper we proposed a new functional form for estimating Lorenz curves, which provides very good fits?with compared to other functional forms, see for example, Kakwani's and Podder's (1973, 76), Rasche's et all (1980), Kakwani's (1980), Gupta's (1984), and Ortega's (1991) functional forms.<span style="mso-spacerun: yes;">  </span>On the basis of the new functional form, we derived the formulae of the Gini, Kakwani, and Chakravarty inequality indices. Empirical verification of the theoretical construct has been done based on the data set from BBS (Bangladesh Bureau of Statistics) publications, "Household Expenditure Survey" corresponding to different years.</span></span></p>