Just a short addendum for the archives if someone should bump into this and
apply it.
The code below works fine, however, to save space, the operation
"*generate independent variables to match wide format"
is not needed since variables not mentioned in the reshape command are
automatically "copied".
/Jan
----- Original Message -----
From: "Scott Merryman" <[email protected]>
To: <[email protected]>
Sent: Thursday, March 04, 2004 5:22 AM
Subject: st: Re: Re: Re: Serial Correlation in system estimator
> Jan,
>
> With -foreach- , -forvalues- and -while- you can cover a lot of looping
type
> needs.
>
> In this case, I believe the following should work:
>
> *rename dependent variable
> local i = 1
> foreach var of varlist ep-rv {
> rename `var' dep`i'
> local i = `i' + 1
> }
>
>
> *generate independent variables to match wide format
> local i = 1
> while `i' <=4 {
> foreach var of varlist x - p {
> gen indep`var'`i' = `var'
> }
> local i = `i' + 1
> }
>
> drop x - p
> gen year = _n
>
> reshape long dep indepx indepz indepa indepp, i(year) j(id)
>
> tsset id year
>
> tab id, gen(D)
>
> *Generate individual intercepts and independent variables
> foreach var1 of varlist D* {
> foreach var2 of varlist indep* {
> gen `var1'`var2' = `var1'*`var2'
> }
> }
>
> aorder
> drop D1indepp D2indepp D3indepa D4indepa D3indepz D4indepz
>
> xtgls dep D* , nocons p(c) corr(psar1)
>
>
> **Example**
>
> Suupose your data looks like this:
>
> . cl, noobs
>
> ep ea eo rv x z
a
> p
> 12.38898 -.1741565 3.10788 9.493736 .1369841 .2551499
.2769154
> .7152805
> 10.04978 1.450661 2.305812 11.04732 .6432207 .0445188
.1180158
> .699069
> 10.30955 .2076075 1.042386 9.105699 .5578017 .4241557
.4079702
> .2322688
> 10.17632 .8222673 3.237755 11.57764 .6047949 .8983462
.7219492
> .0981878
> 12.61388 .4161032 3.531995 11.05705 .684176 .5219247
.871691
> .5948404
> 9.861345 .2186571 2.543519 10.47454 .1086679 .8414094
.4611429
> .3533874
> 10.94411 -.7736335 1.551358 11.09245 .6184582 .2110077
.4216726
> .8071709
> 13.13602 1.216412 1.486686 9.612597 .0610638 .5644092
.8944746
> .1024369
> 10.61442 -.2561719 2.773349 10.91753 .5552388 .2648021
.0580662
> .5773884
> 12.10055 .8602635 2.08501 10.12703 .8714491 .9477426
.6759487
> .1091783
>
> .
> . local i = 1
>
> . foreach var of varlist ep-rv {
> 2. rename `var' dep`i'
> 3.
> . local i = `i' + 1
> 4. }
>
> .
> . local i = 1
>
> . while `i' <=4 {
> 2. foreach var of varlist x - p {
> 3. gen indep`var'`i' = `var'
> 4. }
> 5. local i = `i' + 1
> 6. }
>
> .
> . drop x - p
>
> . gen year = _n
>
> . reshape long dep indepx indepz indepa indepp, i(year) j(id)
> (note: j = 1 2 3 4)
>
> Data wide -> long
> --------------------------------------------------------------------------
---
> Number of obs. 10 -> 40
> Number of variables 21 -> 7
> j variable (4 values) -> id
> xij variables:
> dep1 dep2 ... dep4 -> dep
> indepx1 indepx2 ... indepx4 -> indepx
> indepz1 indepz2 ... indepz4 -> indepz
> indepa1 indepa2 ... indepa4 -> indepa
> indepp1 indepp2 ... indepp4 -> indepp
> --------------------------------------------------------------------------
---
>
> . tsset id year
> panel variable: id, 1 to 4
> time variable: year, 1 to 10
>
> . tab id, gen(D)
>
> id | Freq. Percent Cum.
> ------------+-----------------------------------
> 1 | 10 25.00 25.00
> 2 | 10 25.00 50.00
> 3 | 10 25.00 75.00
> 4 | 10 25.00 100.00
> ------------+-----------------------------------
> Total | 40 100.00
>
> . foreach var1 of varlist D* {
> 2. foreach var2 of varlist indep* {
> 3. gen `var1'`var2' = `var1'*`var2'
> 4. }
> 5. }
>
> .
> . aorder
>
> . drop D1indepp D2indepp D3indepa D4indepa D3indepz D4indepz
>
> . xtgls dep D* , nocons p(c) corr(psar1)
>
> Cross-sectional time-series FGLS regression
>
> Coefficients: generalized least squares
> Panels: heteroskedastic with cross-sectional correlation
> Correlation: panel-specific AR(1)
>
> Estimated covariances = 10 Number of obs =
40
> Estimated autocorrelations = 4 Number of groups =
4
> Estimated coefficients = 14 Time periods =
10
> Wald chi2(14) =
20046.72
> Log likelihood = -34.20722 Prob > chi2 =
0.0000
>
> --------------------------------------------------------------------------
----
> dep | Coef. Std. Err. z P>|z| [95% Conf.
Interval]
> -------------+------------------------------------------------------------
----
> D1 | 10.37989 .703485 14.75 0.000 9.001087
11.7587
> D1indepa | 4.467583 .8529961 5.24 0.000 2.795741
6.139424
> D1indepx | -.4760266 .8182822 -0.58 0.561 -2.07983
1.127777
> D1indepz | -2.232169 .889334 -2.51
0.012 -3.975231 -.4891059
> D2 | .0150844 .4253509 0.04 0.972 -.818588
.8487569
> D2indepa | .8427272 .7865749 1.07 0.284 -.6989314
2.384386
> D2indepx | .5912364 .7011174 0.84 0.399 -.7829283
1.965401
> D2indepz | -.6293221 .7640201 -0.82 0.410 -2.126774
.8681297
> D3 | 2.123046 .575656 3.69 0.000 .9947813
3.251311
> D3indepp | .9182996 .8079717 1.14 0.256 -.6652959
2.501895
> D3indepx | -.1983896 .8707189 -0.23 0.820 -1.904967
1.508188
> D4 | 9.837125 .5677948 17.33 0.000 8.724267
10.94998
> D4indepp | .7172952 .7409337 0.97 0.333 -.7349082
2.169499
> D4indepx | .743207 .7773819 0.96 0.339 -.7804335
2.266848
> --------------------------------------------------------------------------
----
>
> .
> .
> .
> end of do-file
>
> Hope this helps,
> Scott
>
>
>
>
> ----- Original Message -----
> From: "Jan Pettersson" <[email protected]>
> To: <[email protected]>
> Sent: Wednesday, March 03, 2004 1:23 PM
> Subject: st: Re: Re: Serial Correlation in system estimator
>
>
> > Thanks a lot, I guess this will work. However, I have an additional
> > problem...
> > My system has the following form:
> > EP = a10 + a11*X + a12*Z + a13*A
> > EA = a20 + a21*X + a22*Z + a23*A
> > EO = a30 + a31*X + a32*P
> > RV = a40 + a41*X + a42*P
> >
> > Data is now in wide format. As I understand it, I must reshape data into
> > long. In order to "tag" e.g. X to all dependent vars, would it be
correct to
> > first make three "copys" of this variable (as well as one copy of Z, A,
and
> > P) before reshape? I am thinking of:
> >
> > rename EP dep1
> >
> > rename EA dep2
> >
> > rename EO dep3
> >
> > rename RV dep4
> >
> >
> >
> > rename X indeA1
> >
> > rename Z indeB1
> >
> > rename A indeC1
> >
> > rename P indeD1
> >
> >
> >
> > gen indeA2 = indeA1
> >
> > gen indeA3 = indeA1
> >
> > gen indeA4 = indeA1
> > etc.
> >
> > and then:
> > reshape long dep indeA indeB indeC indeD, i(year) j(id)
> >
> > But clearly, there must be a better way of doing this... Any help
> > appreciated.
> > All best,
> > Jan
>
> *
> * For searches and help try:
> * http://www.stata.com/support/faqs/res/findit.html
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
>
*
* For searches and help try:
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