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Re: st: Re: poisson will not converge


From   "Rodrigo A. Alfaro" <ralfaro76@hotmail.com>
To   <statalist@hsphsun2.harvard.edu>
Subject   Re: st: Re: poisson will not converge
Date   Thu, 25 May 2006 00:08:51 -0400

Hi Scott,

LS will be fine. Poisson with fixed-effect is a non-linear estimator that 
needs more attention. I was wonder that fip variable changes over-time but 
not too much, that was the reason why I asked you for a descriptive. I am 
guessing that there is something with this low time variability of flip and 
other variable in the model (probably the fixed-effect). If flip has very 
low time-variability (almost time-invariant) you are not able to identify 
the coefficients in a fixed-effects framework.  Finally, your dependent 
variable seems to have some outlier events... the mean is around 3, 
meanwhile the minimum is 0 and the maximum 99. It would be better for your 
analysis to see the description of the data under the model that you want. 
You can run the LS and take a look of the variables using -xtsum if 
e(sample)-

I hope this helps you
Rodrigo.


----- Original Message ----- 
From: "Scott Cunningham" <scunning@gmail.com>
To: <statalist@hsphsun2.harvard.edu>
Sent: Wednesday, May 24, 2006 12:06 PM
Subject: Re: st: Re: poisson will not converge


On May 24, 2006, at 11:54 AM, Rodrigo A. Alfaro wrote:

> Scott,
>
> What is "fip" variable? state? where did you get 55? It seems this
> variable
> is highly correlated with others in the model. A quick inspection
> could be
> helpful: -xtsum rp srfm age2 hgc hhd1 fip-. Moreover, is this panel
> balanced?

Rodrigo,

Thank you for your reply.  I'll answer what I can.

The panel is balanced (except for hhd1, as I hadn't noticed something
before doing the xtsum [see below]).  "Fip" is a state indicator
variable, and while the number goes to 55, it skips some numbers for
reasons only the Census knows so that it still totals to either 50 or
51 (I forget if DC is included separately).   You say fip is highly
correlated with others in the model.  With other variables in the
model?  You may be right, as when I estimate the model without the -
fip- variables, it does converge fine.  Also, when I re-estimate the
model with fixed effects with just year and fip, it has trouble
converging.  And this is perhaps due to the fact that there is some
migration across time and state within my sample, but not much, as
the individuals in the sample are relatively young and most live in
the same state.  Do you have any suggestions as to what I can do to
overcome this?  Also, OLS does work fine, making me wonder if I
should be suspicious in light of what you said of those estimates.


Variable         |      Mean   Std. Dev.       Min        Max |
Observations
-----------------+-------------------------------------------- 
+----------------
rp       overall |  3.113009   8.069344          0         99 |     N
=    2283
          between |             5.431478          0   44.66667 |
n =     761
          within  |             5.969858  -38.88699   67.11301 |
T =       3
                  |                                            |
srfm     overall |  100.1544   11.52157    35.3187   243.9197 |     N
=    2283
          between |             8.116986   53.33359   172.0538 |
n =     761
          within  |             8.180396   46.42766   184.2222 |
T =       3
                  |                                            |
age2     overall |  308.8257   74.43039        169        529 |     N
=    2283
          between |             47.65699   227.6667   443.6667 |
n =     761
          within  |              57.1899    226.159    394.159 |
T =       3
                  |                                            |
hgc      overall |  10.58826   1.852228          4         16 |     N
=    2283
          between |              1.33929   5.666667   14.66667 |
n =     761
          within  |             1.280086   7.254928   14.25493 |
T =       3
                  |                                            |
hhd1     overall |  .2415459   .4281144          0          1 |     N
=    2277
          between |             .3970831          0          1 |
n =     761
          within  |             .1596349  -.4251208   .9082126 | T-
bar = 2.99212


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