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st: gllamm log-likelihood cycle?

From   Claudio Cruz Cazares <[email protected]>
To   [email protected]
Subject   st: gllamm log-likelihood cycle?
Date   Tue, 28 Oct 2008 12:38:15 +0100

Hi to all,

I am trying to run a two-level multinomial logit with random intercepts. I have a sample of 17'464 observations of 2460 firms, giving and unbalanced panel but with none intermittent missing values.

The model has been running for 21 days and it has not finished yet ! It has done 40 iterations of adaptive quadrature (when I do not include the random intercept it only develops 7 iterations of adaptive quadrature and takes over 18 hours to finish).

I try to add one random intercept for each level of the dependent variable (4 levels). The syntax is (I did not collapse the data) :

tab AID, gen (a)

eq a2: a2
eq a3: a3
eq a4: a4

gllamm AID MED GDE IDVL1 ITEA EDAD PERSOC IPNCL1 IPNFL1 IPNML1 IPNDL1 IPRL1 DM1N NCM1N PX PATTL1 InFIDT , i(Identi) link (mlogit) base (1) fam (binom) nrf (3) eqs (a2 a3 a4) from (a) nocorr trace

I observed that log-likelihood is not really maximizing since the log-likelihood of some iterations are lower than the before one:

Iteration 0:    log likelihood = -12754.365
Iteration 6:    log likelihood = -7105.7245
Iteration 17: log likelihood  = -6572.9334
Iteration 30:  log likelihood = -6486.7566
Iteration 32:  log likelihood = -6486.8283
Iteration 34:  log likelihood = -6480.9099
Iteration 37:  log likelihood = -6487.3043

and so on.

Is that normal? What could I do?. I tried the same model only with 88 firms and after 7 days it still running and with the same problem of the log-likelihood.

Thank you in advance.


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