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Re: st: xtdescribe and panel data
From
Nick Cox <[email protected]>
To
[email protected]
Subject
Re: st: xtdescribe and panel data
Date
Tue, 6 Sep 2011 10:31:39 +0100
On Tue, Sep 6, 2011 at 9:12 AM, A. Berâ <[email protected]> wrote:
> I have some panel data as described below. Few questions:
>
> 1. Can these data be analyzed by panel data methods? I would
> appreciate any suggestions about a suitable approach for these data.
You have panel data. You let slip that the panels are firms. Do
something that makes economic sense.
That seems all that can be advised.
> 2. How can I delete firms that have a specific pattern? For example
> how can I delete these type of firms: 1..........111 ?
You can create a pattern variable like this.
use http://www.stata-press.com/data/r10/xtdatasmpl.dta, clear
xtset idcode year
keep if idcode <= 5
su year, meanonly
local max = r(max)
local min = r(min)
local range = r(max) - r(min) + 1
local miss : di _dup(`range') "."
bysort idcode (year) : gen this = substr("`miss'", 1, year[1]-`min') +
"1" if _n == 1
by idcode : replace this = substr("`miss'", 1, year- year[_n-1] - 1) +
"1" if _n > 1
by idcode : replace this = this + substr("`miss'", 1, `max'-year[_N])
if _n == _N
by idcode : gen pattern = this[1]
by idcode : replace pattern = pattern[_n-1] + this if _n > 1
by idcode : replace pattern = pattern[_N]
tab pattern
xtdes
After that you can do things conditionally on values of -pattern-.
> 3. Is imputation appropriate if "holes" between years is more than one?
You could interpolate. People usually don't with this kind of data.
> Many thanks for any help.
> --
> abdullah berâ
>
>
> . xtdescribe, patterns(1000)
>
> id: 2, 3, ..., 37376 n = 22997
> date: 1996, 1997, ..., 2009 T = 14
> Delta(date) = 1 unit
> Span(date) = 14 periods
> (id*date uniquely identifies each observation)
>
> Distribution of T_i: min 5% 25% 50% 75% 95% max
> 1 1 2 4 9 14 14
>
> Freq. Percent Cum. | Pattern
> ---------------------------+----------------
> 3171 13.79 13.79 | 1.............
> 2447 10.64 24.43 | 11111111111111
> 1932 8.40 32.83 | 11............
> 1471 6.40 39.23 | ...........111
> 1066 4.64 43.86 | ..........1111
<big snip>
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