testTIP: Test for TIP dominance

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

View source: R/testTIP.R

Description

Statistical test procedure given by Xu and Osberg (1998) to study TIP dominance from sample TIP curve estimates.

Usage

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testTIP(dataset1, dataset2, ipuc = "ipuc", hhcsw = "DB090",
  hhsize = "HX040", pz = 0.6, same.arpt.value = NULL, norm = FALSE,
  samplesize = 50, alpha = 0.05)

Arguments

dataset1

a data.frame containing the variables.

dataset2

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".

pz

a number between 0 and 1 which represents the percentage to be used to calculate the at-risk-of-poverty threshold. The default is 0.6.

same.arpt.value

a number that will be used as a common poverty threshold. If NULL, poverty thresholds will be calculated from each datasets (see arpt).

norm

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

samplesize

an integer which represents the number of TIP curve ordinates to be estimated. The default is 50.

alpha

a scalar indicating the significance level. Default is 0.05.

Details

Because the TIP curve becomes horizontal at the arpr value, it is only necessary to have the test implemented over the interval (0, max {arpr1, arpr2}). For that reason both TIP curves are truncated at the same value equal to max{arpr1, arpr2} and ordinates are only compared at points p_i = i/samplesize, where i=1, …, k in the interval (0, max { arpr1, arpr2}) (see arpr function).

The null hypothesis to be tested is that the TIP curve calculated from dataset1 dominates the one calculated from dataset2.

Value

A list with the following components:

Author(s)

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

References

C. M. Beach and S. F. Kaliski (1986) Curve inference with sample weights: and application to the distribution of unemployment experience, Journal of the Royal Statistical Society. Series C (Applied Statistics), Vol. 35, No. 1, 38–45.

D.A. Kodde and F.C. Palm (1986) Wald criteria for jointly testing equality and inequality restrictions, Econometrica, 50, 1243–1248.

F.A. Wolak (1989), Testing inequality constrains in linear econometric models, Journal of Econometrics, 41, 205–235.

K. Xu and L. Osberg (1998) A distribution-free test for deprivation dominance, Econometric Reviews, 17, 415–429.

See Also

OmegaTIP, setupDataset, arpt, arpr

Examples

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data(eusilc2)
ATdataset <- setupDataset(eusilc2, country = "AT")
ATdataset1 <- setupDataset(eusilc2, country = "AT", region = "Burgenland")
ATdataset2 <- setupDataset(eusilc2, country = "AT", region = "Carinthia")
testTIP(ATdataset1, ATdataset2, same.arpt.value = arpt(ATdataset), samplesize = 50, alpha = 0.05)

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