The decomposed PaF income polarization index
paf2(y, a, ncores = 1)For a single value of \(\alpha\), the function returns a vector with the PaF index, the deprivation and the surplus components. If a range of values of \(\alpha\) are given, it will return a matrix with the same components, where each row corresponds to a specific value of \(\alpha\).
A numeric vector with income data.
The value of \(\alpha\). This can either be a number or a vector with many values. In any case, the \(\alpha\) may take values 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 either a specific value, or for a range of values, of \(\alpha\). 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.
colpafs2, paf
y <- rgamma(100, 10, 0.01)
paf(y, 0.25)
paf2( y, 0.25)
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