DER (version 1.3)

Many PaF income polarization indices: Many PaF income polarization indices

Description

Many PaF income polarization indices

Usage

colpafs(y, a, ncores = 1)

Value

A matrix, where each row contains the PaF index, the alienation (twice the Gini index) and identification components and 1 + the normalized covariance.

Arguments

y

A numeric matrix with income data. The PaF index will be computed for each column seperately.

a

The value of \(\alpha\), a number between 0.25 and 1.

ncores

The number of cores to use. If greater than 1, parallel computing will take place. It is advisable to use it if you have many observations and or many variables, otherwise it will slow down the process. The default is 1, meaning that code is executed serially.

Author

Michail Tsagris and Christos Adam.

R implementation and documentation: Michail Tsagris and Christos Adam .

Details

The function compute the PaF index of Duclos, Esteban and Ray (2004) for a specific value of \(\alpha\), for each column of the matrix.

References

Duclos J. Y., Esteban, J. and Ray D. (2006). Polarization: concepts, measurement, estimation. In The Social Economics of Poverty (pp. 54--102). Routledge.

Duclos J. Y., Esteban, J. and Ray D. (2004). Polarization: concepts, measurement, estimation. Econometrica, 72(6): 1737--1772.

See Also

paf, colpafs2

Examples

y <- matrix( rgamma(100 * 10, 10, 0.01), ncol = 10 )
colpafs(y, 0.25)