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Re: st: Autocorrelation tests for FE models


From   Kyle Hood <[email protected]>
To   [email protected]
Subject   Re: st: Autocorrelation tests for FE models
Date   Thu, 04 Jun 2009 19:57:39 -0400

There is no conflict, here. Stata has not reported any standard errors for rho estimated using the xtregar command; this command is not testing for serial autocorrelation, per se, although if you can find a standard error for rho in the e() structure, maybe you can do the test yourself. The other command you report the results for is testing for serial autocorrelation, and we only know the p-value associated with this test. Be careful not to confuse statistical significance and effect size -- both of these commands are telling you different things. The latter test strengthens the argument that xtregar should be used (instead of xtreg, for example).

P K wrote:
Hi,

I test a fixed effects panel model with 61 groups for 10 years and tested for autocorrelation with the xtregar and the xtserial command, which lead to different findings. Xtregar doesn't indicate too high autocorrelation (rho_ar =.12), while xtserial indicates autocorrelation (Woolridge test: Prob > F = 0.0041)

My questions therefore are:
Which test is more "reliable", and what can I do about the autocorrelation indicated by the Woolridge test (how to correct for it)?

Thanks,
Pat


PS: Here is the output for each test:

1) xtregar command in STATA:  rho_ar   .12069893   => doesn't seem to indicate too high autocorrelation

OUTPUT:

FE (within) regression with AR(1) disturbances  Number of obs      =       426
Group variable: number                          Number of groups   =        61

R-sq:  within  = 0.0206                         Obs per group: min =         5
between = 0.0017                                        avg =       7.0
overall = 0.0011                                        max =         8

F(6,359)           =      1.26
corr(u_i, Xb)  = -0.8001                        Prob > F           =    0.2762


AverCh~Eadj2       Coef.   Std. Err.      t    P>t     [95% Conf. Interval]

duration_c~e   -.4899444    .687246    -0.71   0.476    -1.841478    .8615894
sizelnempl   -1.867376   2.287751    -0.82   0.415    -6.366453      2.6317
age   -.0368308   .2794663    -0.13   0.895    -.5864275    .5127659
prior_slac~2    .4346291   .3607199     1.20   0.229    -.2747605    1.144019
ROEadj_1    .0288556   .0507004     0.57   0.570    -.0708516    .1285627
external_c~y    2.555537   1.347617     1.90   0.059    -.0946773    5.205752
_cons    16.30932   21.37442     0.76   0.446    -25.72549    58.34412

rho_ar   .12069893
sigma_u   6.6460257
sigma_e   12.876146
rho_fov   .21036696   (fraction of variance because of u_i)

F test that all u_i=0:     F(60,359) =     0.49              Prob > F = 0.9994


3) xtserial command in STATA: Woolridge test indicates that there is autocorrelation

OUTPUT:
Linear regression                                      Number of obs =     414
F(  6,    60) =    2.31
Prob > F      =  0.0450
R-squared     =  0.0252
Root MSE      =  16.212

(Std. Err. adjusted for 61 clusters in number)

Robust
D. AverCh~Eadj2 Coef. Std. Err. t P>t [95% Conf. Interval]

duration_c~e D1. .3378522 .8894139 0.38 0.705 -1.441241 2.116945 ukdum D1. (dropped) frendum D1. (dropped) sizelnempl D1. -4.680739 2.989539 -1.57 0.123 -10.66071 1.299229 age D1. -.3837846 .391899 -0.98 0.331 -1.167699 .4001301 prior_slac~2 D1. .2684736 .315091 0.85 0.398 -.3618022 .8987494 ROEadj_1 D1. .1397712 .0695373 2.01 0.049 .000676 .2788664 external_c~y D1. 1.648788 1.834245 0.90 0.372 -2.020249 5.317824


Woolridge test for autocorrelation in panel data
H0: no first-order autocorrelation
F(  1,      60) =      8.903
Prob > F =      0.0041


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--
Kyle Hood
Department of Economics
Yale University
New Haven, CT
website: http://www.econ.yale.edu/~kkh25/

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