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Re: st: rectangulizing data
From
Joerg Luedicke <[email protected]>
To
[email protected]
Subject
Re: st: rectangulizing data
Date
Thu, 26 May 2011 12:10:13 -0400
On Thu, May 26, 2011 at 11:19 AM, Dmitriy Krichevskiy
<[email protected]> wrote:
> Dear Listers,
> I am trying to figure out the simplest way to covert a large panel
> dataset from monthly to annual income. The income is only reported
> monthly and I would want to clean the data of anyone missing a month
> in a particular year. I would like to drop observations for that
> person-year only and keep that person if they are fully present in
> some other year. Here is an equivalent data structure. As always, that
> a lot for your help.
> Dmitriy
>
> ID Month Income
> 1 1 1000
> 1 2 500
> 1 3 1000
> 1 13 0
> 1 14 0
> 1 15 0
> 1 16 0
> 1 17 600
> 1 18 1000
> 1 19 1000
> 1 20 1000
> 1 21 1000
> 1 22 1000
> 1 23 660
> 1 24 800
> 1 25 1200
> 2 1 2400
> 2 2 2400
> 2 5 2600
As Oliver already mentioned, your example data is confusing. Anyway,
if I understand you right you want to drop 12 months that fall into a
calendar year (I assume) when valid income data is only available for
a number of months < 12? So, for example, if ID X has 10 month of
income data in year Y, you want to drop year Y entirely for that ID? I
feel it is hard to imagine circumstances in which that would make a
lot of sense as you would discard a ton of information for no apparent
reason. I would think even a simple imputation approach would fare
better here (for example, by replacing the missing data with
information on income from a previous month). In any case, what is the
reason for missingness of income information here?
J.
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