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Re: st: GMM estimation.

From   Usman Gilani <>
Subject   Re: st: GMM estimation.
Date   Thu, 03 Jan 2013 19:22:00 +0000

Thanks everyone,

@JVVerkuilen yeah it's quite challenging for me as i'm new to econometrics and Stata. I'm already following your advice. and I'll update statalisters  as soon as i manage to run this model.

@Nick, thanks for your reply. 
1. Well i'm not ignoring Al advice, I just didn't get how he did the reparametrization of the model. if i follow his model that has 7 parameters {A0..A6} where {A0} = {a0}*{a1} etc. then how i can tell Stata that parameter {A0} is a product of two parameters i.e. {a0}*{a1}. 

2. I'm following JVerkuilen method of running the simple model. 

3. the error term  DP*{a0}*e_(it). i get after substituting eq.(2) and eq.(3) in eq(1).  and this is quite new to me that the error term is consisting of variable and a parameter. I have seen some models in which error term is depending on parameter but could't find this case ( in which error term is depending on variable and a parameter).
If you have seen any research paper with this kind of model please let me know.

4. I'm quiet new to econometrics this thing is holding me understanding the model. So I'm studying hard to understand the theory behind it.


On 3 Jan 2013, at 18:36, JVerkuilen (Gmail) <> wrote:

> On Thu, Jan 3, 2013 at 6:30 AM, Usman Gilani <> wrote:
>> my question, is that the correct way to input the equation ? because STATA
>> giving me the error message "could not calculate numerical derivatives --
>> flat or discontinuous region encountered"
>> please suggests me how can I perform this estimation
> As I said previously, this model is so complex it's next to impossible
> to diagnose what's going wrong. You have so many failure points
> there's no telling where it's breaking. Just a guess but I suspect
> that it's unidentified, but tracking that down will not be easy. It
> could also be that you are giving it bad starting values and it's
> diverging.
> Simplify dramatically and build up. Find an example of the kind of
> model you want to run that has only one or two variables in it using
> data that you know work. Never mind that it's not the model you want
> to run. Gain experience with specifying it in -gmm- syntax and seeing
> situations of what a working model looks like and then translate that
> over to a one or two variable subset of your data. Then build up to
> the model you want to run. If it crashes on only one or two variables
> then it's not identified. If it starts diverging or performing badly
> as you add variables, chances are good that you have an empirical
> identification issue (i.e., insufficient data). You can explore this
> by using simulated datasets.
> If you look at how Stata estimates a model such as -xtmelogit- it does
> exactly this strategy to generate good starting values.
> Yes, this seems like a pain in the zxx, but it's the only thing that
> works. These kinds of nonlinear models are simply not easy to work
> with and require a lot from the user.
> -- 
> JVVerkuilen, PhD
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