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From |
Usman Gilani <u.gilani@icloud.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: GMM estimation. |

Date |
Fri, 04 Jan 2013 21:06:52 +0000 |

Dear members, Finally I managed to run the model. the problem was that I was giving the wrong initial values for parameters. Now this is what I'm getting but I'm worried it's going to be around 3 hours now and it stuck at step 2 iteration 3. but the Stata showing that the program is running. my question is should I wait or stop the process and check the model again? . gmm (r1-({a0=0.5}*{a1=0.42}*w1*DP+(1-{a0}*DP)*lr1+{a0}*{a2=0.16}*DP*w2+{a0}*{a3= -0.013}*DP*w > 3+{a0}*{a4= -0.026}*DP*y1+{a0}*{a5= 0.081}*DP*y2+{a0}*{a6= -0.660}*DP*y3)), xtinstruments(w1 > w2 w3 y1 y2 y3 DP, lags(1/2)) winitial(xt L) warning: 478 missing values returned for equation 1 at initial values Step 1 Iteration 0: GMM criterion Q(b) = .15918243 Iteration 1: GMM criterion Q(b) = .0002628 Iteration 2: GMM criterion Q(b) = .00018952 Iteration 3: GMM criterion Q(b) = .00018952 Step 2 Iteration 0: GMM criterion Q(b) = .06458347 Iteration 1: GMM criterion Q(b) = .04372914 Iteration 2: GMM criterion Q(b) = .04367703 Iteration 3: GMM criterion Q(b) = .04367703 On 3 Jan 2013, at 19:36, Nick Cox <njcoxstata@gmail.com> wrote: > I will just address Usman Gilani's comments on my original #1 and #3: > > 1. Al's re-parameterisation is not one-to-one. It would be pointless > if it were, at most a change of symbolism or notation. If you want to > insist on your parameterisation, you can't do what he suggests, but > estimation is going to be way more difficult. > > 3. I can't help here on literature -- as I signalled, this is not my > field -- but you should note that your code is not postulating the > same error structure as your equations. > > Nick > > On Thu, Jan 3, 2013 at 7:22 PM, Usman Gilani <u.gilani@icloud.com> wrote: >> 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. >> >> regards, >> Gilani. >> >> >> >> >> >> On 3 Jan 2013, at 18:36, JVerkuilen (Gmail) <jvverkuilen@gmail.com> wrote: >> >>> On Thu, Jan 3, 2013 at 6:30 AM, Usman Gilani <u.gilani@icloud.com> 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. > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/faqs/resources/statalist-faq/ > * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**References**:**st: GMM estimation.***From:*Usman Gilani <u.gilani@icloud.com>

**Re: st: GMM estimation.***From:*"JVerkuilen (Gmail)" <jvverkuilen@gmail.com>

**Re: st: GMM estimation.***From:*Usman Gilani <u.gilani@icloud.com>

**Re: st: GMM estimation.***From:*Nick Cox <njcoxstata@gmail.com>

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