 |
[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]
Re: st: Panel Data-FIXED, RANDOM EFFECTS and Hausman Test
|
From |
Muhammad Billal Malik <[email protected]> |
|
To |
[email protected] |
|
Subject |
Re: st: Panel Data-FIXED, RANDOM EFFECTS and Hausman Test |
|
Date |
Thu, 26 Feb 2009 21:40:58 +0000 |
Thanks Kirimi, Just to explain. The question I want to answer is that
if variable lx2 has a statistically significant impact on my dependant
variable ly.
My model is: ln GDPit = â0it + â1 ln FDI it + â2 InTRP it + â3 ln
NBT it + â4 SEC it + â5 EFI it + â6 GFCit + eit (Equation 1)
GDP = Gross domestic Product
FDI = Foreign Direct Investment
TRP= Tourism receipts
NBT= Net Barter terms of Trade
SEC= % Children in secondary education
EFI = Economic Freedom Index
GFC = Gross Fixed Capital as a % of GDP
I have 12 Sub-Saharan african Countries, so from my basic
understanding of econometrics, I don't think I will have a problem
with heterogeneity? Please correct me if I am wrong.
How would I be able to tell if I am having data problems from the
pooled data, and why will the within effects not show me much (I
thought the fixed effects within estimator is usually the more
appropriate method?
Kind Regards,
Mohammud
On Thu, Feb 26, 2009 at 9:24 PM, Kirimi Sindi <[email protected]> wrote:
> 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
>>
>> *
>> * 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/
>>
>>
>>
>
> --
> *******************************
> 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/
>
*
* 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/