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Re: st: Household-fixed effect model with 50,000 hh
From
Shikha Sinha <[email protected]>
To
[email protected]
Subject
Re: st: Household-fixed effect model with 50,000 hh
Date
Fri, 5 Nov 2010 18:42:54 -0400
Dear Maarten,
I used xi and xtreg for comparing the results on a smaller sample. The
estimated coefficients are similar in both the approaches. However,
why the R-square is different in tow approaches. for example, in -xi
R-square is 0.0344, but in -xtreg it is 0.0247.
xi: reg literate treatvar scdum stdum femaledum i.yob
i.yob _Iyob_1981-1997 (naturally coded; _Iyob_1981 omitted)
Source | SS df MS Number of obs = 1099940
-------------+------------------------------ F( 20,1099919) = 1956.49
Model | 5656.22324 20 282.811162 Prob > F = 0.0000
Residual | 158993.3461099919 .14455005 R-squared = 0.0344
-------------+------------------------------ Adj R-squared = 0.0343
Total | 164649.5691099939 .149689728 Root MSE = .3802
------------------------------------------------------------------------------
literate | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
treatvar | .0096066 .0016626 5.78 0.000 .006348 .0128651
scdum | -.0717236 .0009867 -72.69 0.000 -.0736574 -.0697897
stdum | -.0833864 .0009866 -84.52 0.000 -.0853202 -.0814526
femaledum | -.0917641 .0007255 -126.49 0.000 -.093186 -.0903422
_Iyob_1982 | -.0715752 .003113 -22.99 0.000 -.0776765 -.065474
_Iyob_1983 | .0077746 .0031037 2.50 0.012 .0016914 .0138578
_Iyob_1984 | -.0441444 .0028554 -15.46 0.000 -.0497409 -.038548
_Iyob_1985 | .0219268 .0030655 7.15 0.000 .0159185 .0279352
_Iyob_1986 | -.0027881 .0029753 -0.94 0.349 -.0086196 .0030433
_Iyob_1987 | .0129593 .0031674 4.09 0.000 .0067513 .0191672
_Iyob_1988 | .0268027 .0033661 7.96 0.000 .0202052 .0334002
_Iyob_1989 | .0364277 .0033757 10.79 0.000 .0298115 .0430439
_Iyob_1990 | .0396838 .0033278 11.92 0.000 .0331614 .0462061
_Iyob_1991 | .0736859 .0034076 21.62 0.000 .0670072 .0803646
_Iyob_1992 | .0300572 .0032963 9.12 0.000 .0235966 .0365178
_Iyob_1993 | .0589573 .0034205 17.24 0.000 .0522533 .0656614
_Iyob_1994 | -.0018679 .0033077 -0.56 0.572 -.0083509 .0046151
_Iyob_1995 | -.0353471 .0033853 -10.44 0.000 -.0419821 -.0287121
_Iyob_1996 | -.0029324 .0035607 -0.82 0.410 -.0099113 .0040465
_Iyob_1997 | -.0723428 .0036368 -19.89 0.000 -.0794708 -.0652148
_cons | .8737828 .0026022 335.78 0.000 .8686825 .8788831
------------------------------------------------------------------------------
. xtset yob
panel variable: yob (unbalanced)
. xtreg literate treatvar scdum stdum femaledum,fe
Fixed-effects (within) regression Number of obs = 1099940
Group variable: yob Number of groups = 17
R-sq: within = 0.0235 Obs per group: min = 21986
between = 0.2733 avg = 64702.4
overall = 0.0247 max = 94937
F(4,1099919) = 6629.09
corr(u_i, Xb) = 0.0407 Prob > F = 0.0000
------------------------------------------------------------------------------
literate | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
treatvar | .0096066 .0016626 5.78 0.000 .006348 .0128651
scdum | -.0717236 .0009867 -72.69 0.000 -.0736574 -.0697897
stdum | -.0833864 .0009866 -84.52 0.000 -.0853202 -.0814526
femaledum | -.0917641 .0007255 -126.49 0.000 -.093186 -.0903422
_cons | .8813938 .0013269 664.25 0.000 .8787931 .8839944
-------------+----------------------------------------------------------------
sigma_u | .04135333
sigma_e | .38019738
rho | .01169217 (fraction of variance due to u_i)
------------------------------------------------------------------------------
F test that all u_i=0: F(16, 1099919) = 565.84 Prob > F = 0.0000
Thanks,
Shikha
On Thu, Nov 4, 2010 at 3:59 AM, Maarten buis <[email protected]> wrote:
> --- On Wed, 3/11/10, Shikha Sinha wrote:
>> Let child ID is cid and household id is hhid and data are
>> child-level observation within the households, and I want
>> to estimate a household-fixed effect model, then What is
>> the difference among these three estimation or are they same?
>>
>> 1. xi: reg y x1 x2 i.hhid
>>
>> 2. sort cid hhid
>> tsset cid hhid
>> xtreg y x1 x2, fe
>>
>> 3. xi:xtreg y x1 x2 i.hhid, fe
>
> 1. is in principle ok, but you said earlier that your data
> contains too many households for Stata to be able to estimate
> that model.
>
> 2. is wrong for your purpose, you want to use -xtset- not
> -tsset-.
>
> 3. is wrong also, the whole point of -xtreg- is that that
> way you can avoid making those dummies.
>
>
> Instead you should use:
>
> xtset hhid
> xtreg y x1 x2, fe
>
> For more information read -help xtreg- and -help xtset-.
>
> Hope this helps,
> Maarten
>
> --------------------------
> Maarten L. Buis
> Institut fuer Soziologie
> Universitaet Tuebingen
> Wilhelmstrasse 36
> 72074 Tuebingen
> Germany
>
> http://www.maartenbuis.nl
> --------------------------
>
>
>
>
>
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