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From |
Xiang Ao <[email protected]> |

To |
"[email protected]" <[email protected]> |

Subject |
Re: st: RE: overidentification test after treatreg |

Date |
Fri, 22 Oct 2010 14:09:53 -0400 |

Hi Mark, Thanks for the explanation. One other question I have on your example "turn = a + b*foreign + c*mpg foreign = d + e*mpg The just-identified system is turn = a + b*foreign foreign = d + e*mpg"

E(lambda*z)=0 (for probit) E(residual*x)=0 (for second stage OLS)

Xiang On 10/22/2010 01:37 PM, Schaffer, Mark E wrote:

Xiang,`-----Original Message----- From: [email protected] [mailto:[email protected]] On Behalf Of Xiang Ao Sent: 22 October 2010 18:06 To: [email protected] Subject: Re: st: RE: overidentification test after treatreg Thank you, Mark, for the prompt reply. I guess my question is still why this would tell you the robustness of instruments?`

It tells you only what any overidentification test tells you, namely, are the identifying restrictions supported by the data?The reason we can do a LR test is because of the nonlinearity of the selection process (probit).True. The probit selection equation means there's only one way to specify a just-identified model.Think of a 2sls setting, we cannot do something like that since there has to be excluded instrument(s), otherwise it's unidentified.Not so. The standard Hansen-Sargan overid test is the same thing as a GMM distance test between an overidentified model and a just-identified model. We're doing the same thing, transplanted to treatreg/probit/LR-land.In treatreg, you can have no excluded instruments simply because it's nonlinear. The only identification is through the normality assumption. If your rationale holds, we should be able to do this LR test for any nonlinear model with endogenous regressors, as an overidentification test.True! But I'd be interested to know if others agree.Also, do you have any idea what went wrong with my gmm codes?Sorry, I had only a quick look but couldn't work it out. --MarkThanks, Xiang On 10/22/2010 11:19 AM, Schaffer, Mark E wrote:Xiang,`-----Original Message----- From: [email protected] [mailto:[email protected]] On Behalf Of Xiang Ao Sent: 22 October 2010 15:10 To: [email protected] Subject: st: overidentification test after treatreg Dear Statalisters, I have a question on how to do a Sargan's test after treatreg. I found Mark Schaffer's comments on this question from 2006: http://www.stata.com/statalist/archive/2006-08/msg00804.html In the reply, Mark suggested using a LR test between a full model with all instruments in the second stage and a regular treatreg. My question is: this only tests the hypothesis that all excluded instruments jointly being zero, how would that tell us the robustness of instruments, as Sargan's test would do in an ivreg setting? Mark kindly replied to my email to him and suggested posting to statalist to get more inputs. I am thinking of using gmm to frame the treatreg problem, then Jansen's J would be a byproduct. However, my code with`

gmm does notgenerate consistent estimates with treatreg, which I amsure is dueto my lack of knowledge on this. I post my code here; anysuggestionis greatly appreciated. sysuse auto, clear global xb "{b1}*gear_ratio + {b2}*length + {b3}*headroom + {b0}" global phi "normalden($xb)" global Phi "normal($xb)" global lambda "foreign*$phi/$Phi - (1-foreign)*$phi/(1-$Phi)" global xb2 "{c1}*gear_ratio + {c2}*length + {c3}*headroom + {c0} + {c5}*foreign" gmm (eq1: $lambda) (eq2: turn-$xb2), instruments(eq1: gear_ratio length headroom mpg) instruments(eq2: gear_ratio length headroomforeign )winitial(unadjusted, independent) wmatrix(unadjusted) This is to try to estimate the same model as: treatreg turn gear_ratio length headroom, treat(foreign=gear_ratio length headroom mpg)Here was my rationale for how to do an overid test using an LR statistic. As I wrote it in that Statalist post from 2006 that you cite, I think I got it wrong. Here's my next attempt: Consider a slightly simplified version of your treatreg model: treatreg turn, treat(foreign=mpg) There are two overidentifying restrictions. First, mpgappears in thetreatment equation (foreign) but not in the outcome equation (turn). Second, normality is also an identifying restriction, muchin the sameway as normality can be used in a Heckman selection model as an identifying restriction. Now consider your treatreg model, but with mpg as aregressor in theoutcome equation: treatreg turn mpg, treat(foreign=mpg) This second version is just-identified, with normality as the sole identifying restriction. So, the following should be an LR test of the overidentifying restrctions in your original model: treatreg turn, treat(foreign=mpg) est store troverid treatreg turn mpg, treat(foreign=mpg) est store trjustid lrtest troverid trjustid, df(1) I should also note that this is a system test. The overidentified system is (pardon the terrible shorthand notation): turn = a + b*foreign + c*mpg foreign = d + e*mpg The just-identified system is turn = a + b*foreign foreign = d + e*mpg And your overid test is an LR test of c=0. I *think* this is right, but perhaps you or others on thelist couldcomment. Cheers, MarkBut they don't match. Thank you for your time, Xiang * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/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/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/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**RE: st: RE: overidentification test after treatreg***From:*"Schaffer, Mark E" <[email protected]>

**References**:**st: overidentification test after treatreg***From:*Xiang Ao <[email protected]>

**st: RE: overidentification test after treatreg***From:*"Schaffer, Mark E" <[email protected]>

**Re: st: RE: overidentification test after treatreg***From:*Xiang Ao <[email protected]>

**RE: st: RE: overidentification test after treatreg***From:*"Schaffer, Mark E" <[email protected]>

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