In your case, I will check quadrature with -quadchk- and also I will
estimate the model using -tobit-. My guess is your results from RE with
full set of variables should be similar to the one obtained by a simple
model.
Rodrigo.
-----Mensaje original-----
De: [email protected]
[mailto:[email protected]] En nombre de Michael E
Roettger
Enviado el: Viernes, 10 de Octubre de 2008 09:58 a.m.
Para: [email protected]
Asunto: st: Problem interpreting results from xttobit
Dear STATA list,
I am trying to determine if my (i) regression results are valid using
xttobit and (ii) how to interpret my results due to a major shift in
likelihood functions.
I have been using a random effects tobit model to a measure
left-censored variable [a propensity to commit delinquent acts among a
panel of respondents]. My initial model provides negative log-likehood
with an individual-level random effect that seems reasonable:
>Random-effects tobit regression Number of obs =
2401
>Group variable: aid Number of groups =
804
>Random effects u_i ~ Gaussian Obs per group: min =
2
> avg =
3.0
> max =
3
> Wald chi2(3) =
91.53
>Log likelihood = -4211.3782 Prob > chi2 =
0.0000
.
.
.
> /sigma_u | 2.079586 .2733142 7.61 0.000 1.5439
2.615272
> /sigma_e | 5.835778 .1588994 36.73 0.000 5.524341
6.147215
>-------------+---------------------------------------------------------
>-------------+-------
> rho | .1126776 .0284796 .0662654
.1786233
>-----------------------------------------------------------------------
>-------
However, after adding several variables, the log-likelihood becomes
highly positive and the individual-level random effect that is of the
order of E-39
>Random-effects tobit regression Number of obs =
2294
>Group variable: aid Number of groups =
768
>
>Random effects u_i ~ Gaussian Obs per group: min =
2
> avg =
3.0
> max =
3
>
> Wald chi2(9) =
300.30
>Log likelihood = 52807.689 Prob > chi2 =
0.0000
.
.
.
> /sigma_u | 4.17e-39 1.06e-40 39.19 0.000 3.96e-39
4.38e-39
> /sigma_e | 5.793114 .140685 41.18 0.000 5.517377
6.068852
>-------------+---------------------------------------------------------
>-------------+-------
> rho | 5.19e-79 3.65e-80 4.52e-79
5.95e-79
>-----------------------------------------------------------------------
>-------
Both models converge to a concave solution and I am estimating about 35
quadrature points for the
Gauss-Hermite function. Other than the random effects, the estimated
coefficients for Beta's are
consistent with theory/prior research. Its just the change in likelihood
and a highly significant random effect near zero from the first to the
second models above that leave me scratching my head.
Thanks for your time and help!
Mike Roettger
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