gd_compute_gini_lq: Compute gini index from Lorenz Quadratic fit

In PIP-Technical-Team/wbpip: What the Package Does (One Line, Title Case)

Compute gini index from Lorenz Quadratic fit

Description

gd_compute_gini_lq() computes the gini index from a Lorenz Quadratic fit. Key values is a vector that can be set to fit the follwing formulas: e = -(A + B + C + 1): condition for the curve to go through (1, 1). m = (B^2) - (4 * A). m < 0: condition for the curve to be an ellipse (m is called alpha in paper). n = (2 * B * e) - (4 * C). n is called Beta in paper r = (n^2) - (4 * m * e^2). r is called K in paper.

Usage

gd_compute_gini_lq(A, B, C, key_values)

Arguments

A	numeric: Lorenz curve coefficient. Output of regres_lq()$coef[1].
B	numeric: Lorenz curve coefficient. Output of regres_lq()$coef[2].
C	numeric: Lorenz curve coefficient. Output of regres_lq()$coef[3].
key_values	vector with (e,m,n,r)

Value

numeric

References

Datt, G. 1998. "Computational Tools For Poverty Measurement And Analysis". FCND Discussion Paper 50. World Bank, Washington, DC.

PIP-Technical-Team/wbpip documentation built on Nov. 29, 2024, 6:57 a.m.