ronggui
2005-Jun-04 12:42 UTC
[R] can R do Fixed-effects (within) regression (panel data)?
i want to ask 2 questions.
1) can R do Random-effects GLS regression which i can get from Stata?
the following result is frome Stata.can I get the alike result from R?
xtreg lwage educ black hisp exper expersq married union, re
Random-effects GLS regression Number of obs = 4360
Group variable (i) : nr Number of groups = 545
R-sq: within = 0.1799 Obs per group: min = 8
between = 0.1860 avg = 8.0
overall = 0.1830 max = 8
Random effects u_i ~ Gaussian Wald chi2(14) = 957.77
corr(u_i, X) = 0 (assumed) Prob > chi2 =
0.0000
------------------------------------------------------------------------------
lwage | Coef. Std. Err. z P>|z| [95% Conf.
Interval]
-------------+----------------------------------------------------------------
educ | .0918763 .0106597 8.62 0.000 .0709836 .1127689
......................
d86 | .0919476 .0712293 1.29 0.197 -.0476592 .2315544
d87 | .1349289 .0813135 1.66 0.097 -.0244427 .2943005
_cons | .0235864 .1506683 0.16 0.876 -.271718 .3188907
-------------+----------------------------------------------------------------
sigma_u | .32460315
sigma_e | .35099001
rho | .46100216 (fraction of variance due to u_i)
2)
can R do Fixed-effects (within) regression as Stata's xtreg?
the followng example is from
"Introductory Econometrics: A Modern Approach" by Jeffrey M.
Wooldridge
Chapter 14 - Advanced Panel Data Methods
use http://fmwww.bc.edu/ec-p/data/wooldridge/JTRAIN
iis fcode
tis year
xtreg lscrap d88 d89 grant grant_1, fe
Fixed-effects (within) regression Number of obs = 162
Group variable (i) : fcode Number of groups = 54
R-sq: within = 0.2010 Obs per group: min = 3
between = 0.0079 avg = 3.0
overall = 0.0068 max = 3
F(4,104) = 6.54
corr(u_i, Xb) = -0.0714 Prob > F =
0.0001
------------------------------------------------------------------------------
lscrap | Coef. Std. Err. t P>|t| [95% Conf.
Interval]
-------------+----------------------------------------------------------------
d88 | -.0802157 .1094751 -0.73 0.465 -.2973089 .1368776
d89 | -.2472028 .1332183 -1.86 0.066 -.5113797 .016974
grant | -.2523149 .150629 -1.68 0.097 -.5510178 .046388
grant_1 | -.4215895 .2102 -2.01 0.047 -.8384239 -.0047551
_cons | .597434 .0677344 8.82 0.000 .4631142 .7317539
-------------+----------------------------------------------------------------
sigma_u | 1.438982
sigma_e | .4977442
rho | .89313867 (fraction of variance due to u_i)
------------------------------------------------------------------------------
F test that all u_i=0: F(53, 104) = 24.66 Prob > F =
0.0000
thank you!!
Douglas Bates
2005-Jun-04 14:35 UTC
[R] can R do Fixed-effects (within) regression (panel data)?
On 6/4/05, ronggui <0034058 at fudan.edu.cn> wrote:> i want to ask 2 questions. > > 1) can R do Random-effects GLS regression which i can get from Stata? > the following result is frome Stata.can I get the alike result from R? > > xtreg lwage educ black hisp exper expersq married union, re > > Random-effects GLS regression Number of obs = 4360 > Group variable (i) : nr Number of groups = 545 > > R-sq: within = 0.1799 Obs per group: min = 8 > between = 0.1860 avg = 8.0 > overall = 0.1830 max = 8 > > Random effects u_i ~ Gaussian Wald chi2(14) = 957.77 > corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000 > > ------------------------------------------------------------------------------ > lwage | Coef. Std. Err. z P>|z| [95% Conf. Interval] > -------------+---------------------------------------------------------------- > educ | .0918763 .0106597 8.62 0.000 .0709836 .1127689 > ...................... > d86 | .0919476 .0712293 1.29 0.197 -.0476592 .2315544 > d87 | .1349289 .0813135 1.66 0.097 -.0244427 .2943005 > _cons | .0235864 .1506683 0.16 0.876 -.271718 .3188907 > -------------+---------------------------------------------------------------- > sigma_u | .32460315 > sigma_e | .35099001 > rho | .46100216 (fraction of variance due to u_i) > > > 2) > > can R do Fixed-effects (within) regression as Stata's xtreg? > > the followng example is from > "Introductory Econometrics: A Modern Approach" by Jeffrey M. Wooldridge > Chapter 14 - Advanced Panel Data Methods > > use http://fmwww.bc.edu/ec-p/data/wooldridge/JTRAIN > iis fcode > tis year > xtreg lscrap d88 d89 grant grant_1, fe > > Fixed-effects (within) regression Number of obs = 162 > Group variable (i) : fcode Number of groups = 54 > > R-sq: within = 0.2010 Obs per group: min = 3 > between = 0.0079 avg = 3.0 > overall = 0.0068 max = 3 > > F(4,104) = 6.54 > corr(u_i, Xb) = -0.0714 Prob > F = 0.0001 > > ------------------------------------------------------------------------------ > lscrap | Coef. Std. Err. t P>|t| [95% Conf. Interval] > -------------+---------------------------------------------------------------- > d88 | -.0802157 .1094751 -0.73 0.465 -.2973089 .1368776 > d89 | -.2472028 .1332183 -1.86 0.066 -.5113797 .016974 > grant | -.2523149 .150629 -1.68 0.097 -.5510178 .046388 > grant_1 | -.4215895 .2102 -2.01 0.047 -.8384239 -.0047551 > _cons | .597434 .0677344 8.82 0.000 .4631142 .7317539 > -------------+---------------------------------------------------------------- > sigma_u | 1.438982 > sigma_e | .4977442 > rho | .89313867 (fraction of variance due to u_i) > ------------------------------------------------------------------------------ > F test that all u_i=0: F(53, 104) = 24.66 Prob > F = 0.0000I'm not sure what the models being fit by Stata are but I imagine that they correspond to models that can be fit in R by lmer (package lme4) or lme (package nlme).