Re: st: Juhn-Murphy-Pierce (1993)

["Ben Jann" <ben.jann@gmail.com>]

It is absolutely okay to use weights with -jmpierce-. Simply apply the
weights while estimating the models that serve as input to -jmpierce-.
-jmpierce- will then pick up the weights and appropriately use them in
its calculations.
ben

On 11/27/06, Vora Nakavachara <nakavach@usc.edu> wrote:
> Hi All,
>
> I'm trying to follow Juhn-Murphy-Pierce (1993)
> wage decomposition and have some questions.
>
> If the data I'm using is a survey data (labor force data)
> and it has a weight (sampling weight) attached to each
> observation, then when I do jmpierce do I need to care
> about the weight?
>
> I have read some literature but I don't seem to see anyone
> mentioning anything about this weight.
> (Maybe I'm missing something -- can you please point out
> the literature that discuss it?)
>
> Basically, if I want to calcuate p90-p10 of log wage of people
> in 2000 (and 1995) -- and to describe it as a measure of inequality
> of the country then I need to use weight, right?
>
> So when I decompose how p90-p10 change from 1995 to 2000,
> I should also consider weight?
>
> But, (from the help file of jmpierce)
>
>  y1_i1 = x_i1b + F[-1](p_i1|x_i1) --- for year 2000
>  y1_i2 = x_i2b + F[-1](p_i2|x_i2) --- for year 1995
>
> are "hypothetical" distributions, thus if I am to calculate p90-p10
> (to be used in future steps of the decomposition) from these and
> want to use weight then the weight attached to the observation i
> wouldn't be correct anyway?
>
> So should I just ignore the weight in the decomposition?
> But what about when I want to discuss the summary statistics,
> (as mentioned before) like p90-p10 inequality measure in 2000
> then I believe the weight is important?
>
> Could anyone please help me clarify this?
>
> Thank you very much.
>
> Vora N
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