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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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