Thank you v. much
Os
-----Original Message-----
From: [email protected] [mailto:[email protected]] On Behalf Of G�l �NAL
Sent: Wednesday, June 06, 2007 4:19 PM
To: [email protected]
Subject: Re: st: RE: Normalized Gini coeffient for Negative Income values
Hi Nick and all,
Thank you for your comments. There is a specific method suggested in Chen et. al's paper. I wondered if anyone in this list used it at all. It is used in some research publications by the US Department of Agriculture :
Ashok K. Mishra, Hisham S. El-Osta, Mitchell J. Morehart, James D.
Johnson, and Jeffrey W. Hopkins (2002) Income, Wealth, and the Economic Well-Being of Farm Households. Agricultural Economic Report No. (AER812) 77 pp, July 2002
for those who may be interested here is the link:
http://www.ers.usda.gov/publications/aer812/
It seems common practice among agricultural economists to use an adjusted Gini, but I guess there is not many on the list :), Yours, Gul
On 6/6/07, Nick Cox <[email protected]> wrote:
> There are possible issues on two levels here. First, no Stata
> programmer can write code for a correction that is not specified.
> Perhaps it's specified in the paper. My point in asking for the
> reference was just to remind you of standard Statalist protocol on
> behalf of those people working in the field who might want to know the
> reference. I don't want to read it myself.
>
> Second, on the face of it this suggestion still seems to be intensely
> problematic.
>
> Consider for example another approach to the problem.
> You could always translate by
>
> income' = income - CONSTANT
>
> where CONSTANT is small enough (the empirical minimum, or smaller) to
> ensure that you work with non-negative numbers. But I doubt that there
> is a theoretical way to choose CONSTANT, and even choosing it
> empirically would probably leave you with a distribution whose Gini is
> difficult to compare with any other Gini, unless CONSTANT were the
> same. And if CONSTANT were the same, that would create problems too.
>
> Yet another take is that my impression is that inequality statistics
> hinge on income being a ratio variable, i.e.
> ratios of incomes make sense, so that ratios such as
>
> Bill Gould's income
> -------------------
> Nick Cox's income
>
> are the same whether measured in dollars, pounds, or anything else.
> This is because zero is a natural origin.
> Throw that away and you risk nonsense.
>
> This is all presumption on my part, but I have a strong sense here
> that the proposal you refer to is just hiding the problem. Hiding the
> problem is not the same as solving it.
>
> Nick
> [email protected]
>
> G�l �NAL
>
> > Hi Nick,
> > thank you for the comments, let me make myself more clear then.
> > First on the reference, here is the additional information for those
> > of you who are interested:
> >
> > Chau-Nan Chen Tien-Wang Tsaur; Tong-Shieng Rhai. (1982) The Gini
> > Coefficient and the Negative Income. Oxford Economic Papers
> > (pre-1986); Nov 1982; 34, 3, pp. 473-78
> >
> > On the issue of "fixing the Gini": Chen et al, in their article
> > suggest that when negative incomes are present regular Gini
> > coefficient may overestimate the inequality.
> >
> > I will give the example they use in their article: Consider a
> > community with ten households with the following incomes ( -500,
> > -300, -300, -100, 200, 300, 300, 400, 500, 500). Normal Gini
> > coefficient of such a distribution will be 1.94. When one thinks a
> > case where one household has all the income and all else has nothing
> > Gini is .99, then this 1.94 is an overestimation. Cheun et al.'s
> > suggestion is to correct for this overestimation, which I think is sensible.
> >
> > Thanks for the comments, and I am looking forward to hear incase
> > anyone has any experience with calculating Gini coefficients for
> > datasets with negative incomes,
>
> > On 6/6/07, Nick Cox <[email protected]> wrote:
> > > I have only marginal expertise here, but two comments:
> > >
> > > 1. The reference here is incomplete as you give no author initials
> > > or journal or book details.
> > >
> > > 2. Clearly negative incomes make sense in your context; trying to
> > > fix the Gini as if they didn't exist seems to be a denial of this
> > > and dubious practice.
> > >
> > > Nick
> > > [email protected]
> > >
> > > G�l �NAL
> > >
> > > > I am working with a large dataset which includes agricultural
> > > > households. Households have negative incomes ( since it is
> > > > agricultural production, income can turn negative in some
> > cases). So,
> > > > my problem is that, when I use ineqdec0, to include
> > negative and zero
> > > > values of income, it gives me gini coefficients that is
> > > > sometimes greater than 1 ( which I calculate for 500 villages) .
> > This is normal,
> > > > because as it is discussed in an article by Chen et al. (1982),
> > > > titled: "The Gini coefficient and negative income" the
> > definition of
> > > > the Gini coefficient allows that to happen when there are
> > > > negative incomes. Chen et al. also suggest a way to normalize it
> > so that Gini
> > > > coefficient would be between 0 and 1 only.
> > > >
> > > > Does anyone know a code or a command in Stata that would do
> > > > this, i.e., normalize the Gini coefficient so that when
> > negative incomes are
> > > > in the data, Gini would not be larger than 1. Since I
> > have been using
> > > > ineqdec0 so far, I am not really familiar with the ado
> > file of it, is
> > > > the only way to go and change the do file based on Chen's
> > suggestion
> > > > to normalize it?
>
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--
G�l �NAL
Ph.D. Candidate,
Economics, Umass, Amherst
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