Archive for the ‘Income Dist’ Category

More on Lorenz Curve Interpolation

In the previous post the interpolation was demonstrated using a simulated data. Here we do an application to a real data set. The Data is for Urban China 2004-2005 obtained from PovcalNet website. In what follows we plot the Spline-interpolated curves vs their estimation using GB2 Continue reading

Lorenz Curves: Spline Interpolation

The standard practice of Lorenz curve interpolation relies on linear interpolations where each point is connected to the next one using a straight line. There are of course other ways of interpolation and a natural one is to use splines.  In this post, I introduce an existing package in “R” that can be used to interpolate Lorenz curves and to compute the corresponding CDF and PDF functions. Continue reading

Lorenz Curve Slides

Here are the slides of the “Lorenz Curve” paper I presented on Friday in UWA. I will give link to the full paper soon (some slight edits on the paper is still going on).

Income Density Estimation

All measurements of poverty, inequality and so forth rely in some ways on estimation of a representation of an income (or consumption) distribution. The most commonly used representation is the PDF therefore in this post I review common ways of density estimation. The excellent handbook chapter of Cowell and Flachaire (2015) covers this topic in some details (see also Lubrano 2013). My take here is instead brief, informal, and based on personal experiences. Continue reading

Lorenz Curves 2: Definition and Specification

Inference for Lorenz curves requires its rigorous definition and good specifications. This post briefly discusses alternative definitions and ways of specifying Lorenz curves: Continue reading

Histogram vs Lorenz

Here is a question that might be worth of some thinking. Suppose one has a random sample of say 10000 observations on income of individuals and wants to record just two summary statistics for each of say 20 groups made from this data. What summary statistics should be recorded? Continue reading

Lorenz Curves-1

I am going to write about Lorenz curves and inference about them in a series of posts. This first post tries to explain why there are so much interests in Lorenz curves.

CDF and PDF are the first things come to mind when thinking of a distribution but there is another representation namely the Lorenz curve that is as widely used and estimated (if not more) in some contexts such as income distribution analyses. Here are the reasons that I can think for popularity of Lorenz curves: Continue reading