My issue is that finding quintile cut-off points in R is not giving me the same Asset quintiles for roughly 780 observations. I am assuming that this is because my cut-off points are incorrect.

a) Can the factor score given in the dataset directly be used to make quintiles weighted by hv005/100000 (Wt_nat) in the PR file? If not then how to go about it?

b) If (a) is correct, then what could be the reason why my cut off points differ from the one used to the construct the quintile?

This is what I got using the following:

check_bins$quintile2 <- with(check_bins, cut(hv271,

breaks= wtd.quantile (hv271, q=seq(0,1, by=0.2), na.rm = FALSE, weight = Wt_nat),

include.lowest=TRUE, labels = c(1,2,3,4,5)))

20% -0.92065

40% -0.26808

60% 0.38776

80%. 1.06845

However, this is what was given in the wealth index excel file under Combined national wealth score tab. Are these the cut-off points?

20% -.9294019

40% -.2665299

60% .3948751

80% 1.0727570

I would really appreciate any help in this regard!]]>

Here is the Stata code to construct wealth quintiles as "hv270_test", which you can compare with hv270. This can be applied to any HR file. (HR, not PR.) It should be easy enough to translate into R.

use "xxHRxxFL.DTA" , clear

keep hv001 hv002 hv005 hv012 hv013 hv270 hv271

gen mem = hv012

replace mem = hv013 if mem == 0

gen pwt=mem*hv005

gen wt=pwt/1000000

xtile hv270_test=hv271 [pweight=pwt], nquantiles(5)

tab hv270 hv270_test [iweight=wt]

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Thank you for your swift response. I tried the set of commands you had shared on Stata. However, I still get different quintiles (my assumption is that the cut off points for quintiles are different again).

Please find attached my result by using the HR file. Also, since the wealth quintiles were ass per de jury members, I wanted to know why we are considering defect members as well if there were no dejure members in the household. This is because as per the report, each quintile has 20% of the population (dejure) in each quintile.

I will much appreciate your help in resolving this. ]]>

In virtually all surveys the weighted number of de jure household members will not be EXACTLY the same in all quintiles, because everyone in the same household must be in the same quintile. It is also possible for multiple households to be tied at the same value of the continuous index (hv270) and this is more likely in large surveys, such as those in India. Finally, it is possible that the weights (hv005) were modified in this survey after the quintiles had been constructed. I cannot provide any other explanation for the differences you are observing.

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