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[funtik]

Dear communty,

i have a data set with N=74 and T=47, so I have a panel data set and this is also strong balanced.

In order to find an appropriate model, first, i conduct the Hausman Test and that indicate the use of random effects model

| (b) (B) (b-B) sqrt(diag(V_b-V_B))
| fixed random Difference S.E.
-------------+----------------------------------------------------------------
Inside_Event | -.2731725 -.2725065 -.0006661 .
Q2 | -.6792971 -.6819931 .002696 .
Q3 | -.3889817 -.3869155 -.0020662 .
Q4 | .2907415 .2873648 .0033767 .
Adv1 | .0000203 .0000236 -3.25e-06 1.18e-06
Adv_Sponsor1 | -6.07e-06 -8.17e-06 2.10e-06 .
Adv_Inside1 | .0000384 .0000393 -8.87e-07 .
Adv_Insid~r1 | -9.35e-08 -4.92e-07 3.98e-07 .
Competitor~1 | .0000365 .0000379 -1.37e-06 3.83e-07
Google_Tre~s | .0158409 .0156065 .0002344 .0002866
------------------------------------------------------------------------------
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(9) = (b-B)'[(V_b-V_B)^(-1)](b-B)
= 3.61
Prob>chi2 = 0.9354
(V_b-V_B is not positive definite)

Afterwards I us the Breusch Pagan test and that showed that the random effect model is appropriate

Breusch and Pagan Lagrangian multiplier test for random effects

Ind_Stand[Brand_ID,t] = Xb + u[Brand_ID] + e[Brand_ID,t]

Estimated results:
| Var sd = sqrt(Var)
---------+-----------------------------
Ind_Stand | 250.7955 15.83652
e | 5.665431 2.380217
u | 231.1569 15.20384

Test: Var(u) = 0
chibar2(01) = 69065.76
Prob > chibar2 = 0.0000

Next, i examine the assumptions of autocorrelation, using xtserial command and then hetereskedacsticity with the help of xttest3, but also afterwards test the assumption following the suggestion on the link (http://www.stata.com/support/faqs/st...tocorrelation/).

According to the results both assumption were violated. So I have a panel data with serial autocorrelation and heteroskedasticity and now I have no idea what model would be the most appropriate in this case and what command I can use in Stata.

In the next step I'm going also to integrate a lagged (one lag) DV in my model as control variable. I have also the question, how I can find out, what dynamic panel data model is the best?

Thanks in advance and I hope, dear forum members, that u can help me.

A.