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Re: st: Panel Data-FIXED, RANDOM EFFECTS and Hausman Test
Malik,
Running models is okay but you have to ask yourself what question you
want to answer first. Then the next question is the type of data you
have to enable you answer the question. Then the assumption you make
about the data. Does the data have unobserved heterogeneity and is this
heterogeneity corrected with the X's or not. That helps you choose
between RE of FE. I guess within does not tell you much. But I guess you
have started well by running a pooled model. Then look at the results
and ask yourself what could be going on? Is it an artifact of the data.
Do you have data problems.
Then move on.
Kirimi
Muhammad Billal Malik wrote:
I am having some problems with my econometrics based dissertation. I
doing a panel data on 12 sub-saharan african nations, with 6 variables
over a 17 year time period.
I am using a simple log log model to test to see if one of my
variables lx2 (tourism receipts) has a positive affect on GDP. I have
run a pooled regression, then fixed effects between and within, and
finally a random effects. I have then carried out a Hausman test and
achieved a negative value, which has confused me more. I was wondering
what do I do, as in what model shall I choose? I have attached my
STATA output so you can see if I have gone through the right steps.
I will really appreciate if you can help me,
Kind Regards,
Mohammud
Carrying out a pooled data regression
. regress ly lx1 lx2 lx3 lx4 lx5 lx6
Source | SS df MS Number of obs = 57
-------------+------------------------------ F( 6, 50) = 52.04
Model | 59.1406489 6 9.85677481 Prob > F = 0.0000
Residual | 9.47031674 50 .189406335 R-squared = 0.8620
-------------+------------------------------ Adj R-squared = 0.8454
Total | 68.6109656 56 1.22519581 Root MSE = .43521
------------------------------------------------------------------------------
ly | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
lx1 | .173204 .0545574 3.17 0.003 .0636223 .2827857
lx2 | .0816157 .0737985 1.11 0.274 -.0666129 .2298442
lx3 | 1.207415 .7336368 1.65 0.106 -.2661382 2.680968
lx4 | .8167941 .0985049 8.29 0.000 .6189412 1.014647
lx5 | 4.014936 1.263028 3.18 0.003 1.478069 6.551803
lx6 | .2619006 .2371792 1.10 0.275 -.2144879 .738289
_cons | -20.5465 5.498655 -3.74 0.000 -31.59087 -9.502123
------------------------------------------------------------------------------
. gen country = region
Setting up a panel
. tsset country year, yearly
panel variable: country (strongly balanced)
time variable: year, 1990 to 2006
Carrying out a fixed effects within regression on panel data
. xtreg ly lx1 lx2 lx3 lx4 lx5 lx6, fe
Fixed-effects (within) regression Number of obs = 57
Group variable (i): country Number of groups = 10
R-sq: within = 0.7640 Obs per group: min = 2
between = 0.5507 avg = 5.7
overall = 0.5374 max = 8
F(6,41) = 22.12
corr(u_i, Xb) = 0.5835 Prob > F = 0.0000
------------------------------------------------------------------------------
ly | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
lx1 | -.0075411 .0061342 -1.23 0.226 -.0199293 .0048472
lx2 | .1397473 .0208394 6.71 0.000 .0976612 .1818334
lx3 | -.0471179 .0766965 -0.61 0.542 -.2020095 .1077738
lx4 | .0883038 .0510516 1.73 0.091 -.0147971 .1914046
lx5 | .4423916 .1609951 2.75 0.009 .1172554 .7675278
lx6 | -.0635172 .0380633 -1.67 0.103 -.1403876 .0133532
_cons | 2.404044 .8235133 2.92 0.006 .7409252 4.067163
-------------+----------------------------------------------------------------
sigma_u | .95115353
sigma_e | .03719725
rho | .99847294 (fraction of variance due to u_i)
------------------------------------------------------------------------------
F test that all u_i=0: F(9, 41) = 755.95 Prob > F = 0.0000
. xtreg ly lx1 lx2 lx3 lx4 lx5 lx6, be
Carrying out a fixed effects between regression on panel data
Between regression (regression on group means) Number of obs = 57
Group variable (i): country Number of groups = 10
R-sq: within = 0.0790 Obs per group: min = 2
between = 0.9488 avg = 5.7
overall = 0.7682 max = 8
F(6,3) = 9.26
sd(u_i + avg(e_i.))= .4441503 Prob > F = 0.0477
------------------------------------------------------------------------------
ly | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
lx1 | .5188441 .2315068 2.24 0.111 -.2179138 1.255602
lx2 | -.0061883 .4172493 -0.01 0.989 -1.334062 1.321685
lx3 | .1313838 4.684306 0.03 0.979 -14.77617 15.03894
lx4 | .9508895 .2441334 3.89 0.030 .173948 1.727831
lx5 | 7.621178 7.059213 1.08 0.359 -14.84439 30.08674
lx6 | -.672947 1.417266 -0.47 0.667 -5.183319 3.837425
_cons | -26.37744 19.85242 -1.33 0.276 -89.5567 36.80181
------------------------------------------------------------------------------
. xtreg ly lx1 lx2 lx3 lx4 lx5 lx6, re
Carrying out a random effects regression on panel data
Random-effects GLS regression Number of obs = 57
Group variable (i): country Number of groups = 10
R-sq: within = 0.7556 Obs per group: min = 2
between = 0.6683 avg = 5.7
overall = 0.6327 max = 8
Random effects u_i ~ Gaussian Wald chi2(6) = 94.90
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000
------------------------------------------------------------------------------
ly | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
lx1 | -.0065896 .0077505 -0.85 0.395 -.0217803 .0086011
lx2 | .1253869 .0257565 4.87 0.000 .0749051 .1758687
lx3 | -.0363082 .0969763 -0.37 0.708 -.2263783 .1537619
lx4 | .1554292 .061983 2.51 0.012 .0339448 .2769135
lx5 | .4387479 .2031582 2.16 0.031 .0405652 .8369306
lx6 | -.0456517 .0477556 -0.96 0.339 -.1392509 .0479475
_cons | 2.241371 1.053202 2.13 0.033 .1771336 4.305609
-------------+----------------------------------------------------------------
sigma_u | .44383293
sigma_e | .03719725
rho | .99302502 (fraction of variance due to u_i)
------------------------------------------------------------------------------
Fixed-effects (within) regression Number of obs = 57
Group variable (i): country Number of groups = 10
R-sq: within = 0.7640 Obs per group: min = 2
between = 0.5507 avg = 5.7
overall = 0.5374 max = 8
F(6,41) = 22.12
corr(u_i, Xb) = 0.5835 Prob > F = 0.0000
------------------------------------------------------------------------------
ly | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
lx1 | -.0075411 .0061342 -1.23 0.226 -.0199293 .0048472
lx2 | .1397473 .0208394 6.71 0.000 .0976612 .1818334
lx3 | -.0471179 .0766965 -0.61 0.542 -.2020095 .1077738
lx4 | .0883038 .0510516 1.73 0.091 -.0147971 .1914046
lx5 | .4423916 .1609951 2.75 0.009 .1172554 .7675278
lx6 | -.0635172 .0380633 -1.67 0.103 -.1403876 .0133532
_cons | 2.404044 .8235133 2.92 0.006 .7409252 4.067163
-------------+----------------------------------------------------------------
sigma_u | .95115353
sigma_e | .03719725
rho | .99847294 (fraction of variance due to u_i)
------------------------------------------------------------------------------
F test that all u_i=0: F(9, 41) = 755.95 Prob > F = 0.0000
. estimates store fixed
. xtreg ly lx1 lx2 lx3 lx4 lx5 lx6, re
Random-effects GLS regression Number of obs = 57
Group variable (i): country Number of groups = 10
R-sq: within = 0.7556 Obs per group: min = 2
between = 0.6683 avg = 5.7
overall = 0.6327 max = 8
Random effects u_i ~ Gaussian Wald chi2(6) = 94.90
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0000
------------------------------------------------------------------------------
ly | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
lx1 | -.0065896 .0077505 -0.85 0.395 -.0217803 .0086011
lx2 | .1253869 .0257565 4.87 0.000 .0749051 .1758687
lx3 | -.0363082 .0969763 -0.37 0.708 -.2263783 .1537619
lx4 | .1554292 .061983 2.51 0.012 .0339448 .2769135
lx5 | .4387479 .2031582 2.16 0.031 .0405652 .8369306
lx6 | -.0456517 .0477556 -0.96 0.339 -.1392509 .0479475
_cons | 2.241371 1.053202 2.13 0.033 .1771336 4.305609
-------------+----------------------------------------------------------------
sigma_u | .44383293
sigma_e | .03719725
rho | .99302502 (fraction of variance due to u_i)
------------------------------------------------------------------------------
. estimates store random
Carrying out a HAUSMAN TEST
. hausman fixed random
---- Coefficients ----
| (b) (B) (b-B) sqrt(diag(V_b-V_B))
| fixed random Difference S.E.
-------------+----------------------------------------------------------------
lx1 | -.0075411 -.0065896 -.0009515 .
lx2 | .1397473 .1253869 .0143604 .
lx3 | -.0471179 -.0363082 -.0108097 .
lx4 | .0883038 .1554292 -.0671254 .
lx5 | .4423916 .4387479 .0036437 .
lx6 | -.0635172 -.0456517 -.0178655 .
------------------------------------------------------------------------------
b = consistent under Ho and Ha; obtained from xtreg
B = inconsistent under Ha, efficient under Ho; obtained from xtreg
Test: Ho: difference in coefficients not systematic
chi2(6) = (b-B)'[(V_b-V_B)^(-1)](b-B)
= -4.12 chi2<0 ==> model fitted on these
data fails to meet the asymptotic
assumptions of the Hausman test;
see suest for a generalized test
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--
*******************************
Imagination is more important than knowledge.
For while knowledge defines all we currently know and understand,
imagination points to all we might yet discover and create.
*******************************
Kirimi Sindi
PhD Candidate
Department of Agricultural,
Food, and Resource Economics
Room 20 Cook Hall
Michigan State University
East Lansing, MI 48824
Telephone: +1-517-353-5320
Home Tel : +1-517-355-8151
Fax: +1-517-432-1800
*
* For searches and help try:
* http://www.stata.com/help.cgi?search
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/