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Re: st: Panel Data-FIXED, RANDOM EFFECTS and Hausman Test
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From |
Muhammad Billal Malik <[email protected]> |
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To |
[email protected] |
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Subject |
Re: st: Panel Data-FIXED, RANDOM EFFECTS and Hausman Test |
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Date |
Thu, 26 Feb 2009 21:49:13 +0000 |
I am sorry David, but I have not been taught that in my Basic
Econometric course, will it be easy to understand and run?
On Thu, Feb 26, 2009 at 9:26 PM, David Greenberg <[email protected]> wrote:
> With a small number of nations and more years than nations you may be better off using panel-corrected standard errors than the approach you are taking. David Greenberg, Sociology Department, New York University
>
> ----- Original Message -----
> From: Muhammad Billal Malik <[email protected]>
> Date: Thursday, February 26, 2009 2:20 pm
> Subject: st: Panel Data-FIXED, RANDOM EFFECTS and Hausman Test
> To: [email protected]
>
>
>> 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
>>
>> *
>> * 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/
> *
> * 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/
>
*
* For searches and help try:
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* http://www.ats.ucla.edu/stat/stata/