Many decomposed PaF income polarization indices
colpafs2(y, a, ncores = 1)A matrix, where each row contains the PaF index, the deprivation and the surplus components.
A numeric matrix with income data. The PaF index will be computed for each column seperately.
The value of \(\alpha\), a number between 0.25 and 1.
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.
Michail Tsagris and Christos Adam.
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr and Christos Adam econp266@econ.soc.uoc.gr.
The function compute the decomposed PaF index of Duclos, Esteban and Ray (2004) for a specific value of \(\alpha\), for each column of the matrix. The decomposition is with respect to the deprivation and surplus components as suggested by Araar (2008).
Araar A. (2008). On the Decomposition of Polarization Indices: Illustrations with Chinese and Nigerian Household Surveys. CIRPEE Working Paper No. 08-06. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1136142
Duclos J. Y., Esteban, J. and Ray D. (2004). Polarization: concepts, measurement, estimation. Econometrica, 72(6): 1737--1772.
paf2, colpafs
y <- matrix( rgamma(100 * 10, 10, 0.01), ncol = 10 )
colpafs2(y, 0.25)
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