tip: TIP curve

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/tip.R

Description

Estimates TIP curve ordinates. The TIP curve is defined by plotting the cumulated proportion of population on the x-axis and the cumulated per capita poverty gap (the distance between each income and the poverty threshold) on the y-axis from the biggest one downwards.

Usage

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tip(dataset, ipuc = "ipuc", hhcsw = "DB090", hhsize = "HX040",
  arpt.value = NULL, samplesize = 50, norm = FALSE, plot = FALSE)

Arguments

dataset

a data.frame containing the variables.

ipuc

a character string indicating the variable name of the income per unit of consumption. Default is "ipuc".

hhcsw

a character string indicating the variable name of the household cross-sectional weight. Default is "DB090".

hhsize

a character string indicating the variable name of the household size. Default is "HX040".

arpt.value

the at-risk-of-poverty threshold to be used (see arpt). Default is NULL which calculates arpt with default parameters.

samplesize

an integer which specifies the number of (equally spaced) percentiles to be used in the estimation of the TIP ordinates The default is 50. If samplesize is set to ”complete”, ordinates are computed in each value along the whole distribution.

norm

logical; if TRUE, the normalised TIP curve ordinates are computed using the normalised poverty gaps (poverty gaps divided by the poverty threshold).

plot

logical; if TRUE plots the TIP curve.

Details

The TIP (Three I's of Poverty) curve ordinates are computed using the equivalised disposable income. The equivalence scales that can be employed are the modified OECD scale or the parametric scale of Buhmann et al. (1988). The default is the modified OECD scale (see setupDataset).

Value

A data.frame with the following components:

x.tip vector of cumulated proportion of population.

y.tip vector with values of tip curve ordinates.

Author(s)

A. Berihuete, C.D. Ramos and M.A. Sordo

References

B. Buhmann et al. (1988) Equivalence scales, well-being, inequality and poverty: sensitivity estimates across ten countries using the Luxembourg Income Study (LIS) database, Review of Income and Wealth, 34, 115–142.

S.P. Jenkins and P.J. Lambert (1997) Three I's of poverty curves, with an analysis of UK poverty trends, Oxford Economic Papers, 49, 317–327.

See Also

setupDataset, arpt

Examples

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data(eusilc2)
ATdataset <- setupDataset(eusilc2, country = "AT")
tip.curve <- tip(ATdataset, arpt.value = arpt(ATdataset), norm = TRUE)
str(tip.curve)

rtip documentation built on April 12, 2018, 5:04 p.m.