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From |
kokootchke <kokootchke@hotmail.com> |

To |
statalist <statalist@hsphsun2.harvard.edu> |

Subject |
RE: st: Sample selection and endogeneity (or, combining heckman and ivreg) |

Date |
Thu, 6 Aug 2009 02:30:01 -0400 |

Austin Nichols wrote: > Shehzad's code has some typos (compare the if qualifiers), I think, > and without a ref or a proof of consistency, I can't see how anyone > would get those kinds of results published. To be able to trust them > yourself, you would also want to run some simulations to assess finite > sample performance for samples that look like yours (with true coefs > picked to be near your estimated coefs). Austin, thank you very much for your response. I agree that not having a reference would weaken my results and this is why I'm trying to see if someone in this Stata group can point in the right direction. I have thought about the simulations as well and I'm contemplating doing that, but I've never done this before and would like some pointers as to where I should start. Would you have any suggestions or do you have a reference that could help in that regard? Also, what do you mean by "for samples that look like yours"? > Also, note that the original > poster specifies panel data, though what the DGP is, I do not know. > Note in particular that the dependent var is a weighted average of > spreads for one or multiple bonds in a given quarter but a weighted > average of a nonnegative (skewed?) variable is not guaranteed to have > any desirable properties. Also, still assuming that the dep var is > nonnegative or strictly positive, OLS and heckman are inappropriate, > relative to a GLM type model. Presumably, the new GMM models in Stata > 11 are a good place to turn, assuming suitable moments can be > specified. This is a very good point. I have also never used GLM/GMM in this context before, so could you please be more specific regarding what I need to know or where I should look in order to consider this option and try to implement it? Thank you very much once again! Adrian > > On Wed, Aug 5, 2009 at 4:52 AM, Shehzad Ali wrote: >> To add to John's response, if your endogenous variable is binary, then I would use the following: >> >> probit y1 x1 x2 x3 >> predict xbeta1, xb >> gen imills1=normd(xb)/normprob(xb) if y1==1 >> replace imills1=-normd(xb)/(1-normprob(xb)) if y2==0 >> >> heckman y2 y1 $yvar $zvar imills1 [pw=weight], sel(selection_probit= y1 $xvar imills1) cluster(commune) mills(imr2) >> >> I have assumed that the endogenous var is endogenous in both selection and outcome equation. >> Regards, >> Shehzad >> >> >> ----- Original Message ---- >>> From: John Antonakis >>> To: statalist@hsphsun2.harvard.edu >>> Sent: Wednesday, August 5, 2009 7:18:14 AM >>> Subject: Re: st: Sample selection and endogeneity (or, combining heckman and ivreg) >>> >>> Hi: >>> >>> One possibility is to manually obtain predicted values of the endogenous >>> variables (using regress), which will give you consistent estimates. >>> Then use the predicted values in the Heckman model and bootstrap the >>> standard errors. >>> >>> HTH, >>> John. >>> >>> On 05.08.2009 04:51, kokootchke wrote: >>>> Dear all, >>>> >>>> I am trying to estimate an equation in which the dependent variable is only >>> observed when a selection rule applies (your typical sample selection problem a >>> la Heckman). One of the independent variables in the main equation is >>> endogenous, and I'd like to use instrumental variables to address that issue >>> within the Heckman framework. >>>> >>>> I haven't been able to find any papers or references that deal with this >>> issue, especially because I have a panel dataset containing 40+ countries and >>> about 60 time periods (quarters). My approach is to run the selection probit, >>> then use the predicted values in a 2SLS framework. I guess I'd have to do some >>> standard-error correction (any hints on this would also be useful)... but I >>> wanted to ask if you guys could tell me whether there is a Stata command that >>> does this or if there are any references you could suggest? >>>> >>>> For more information on my particular case, please see below. >>>> >>>> Thanks! >>>> Adrian >>>> >>>> >>>> p.s. A few more details on my model: >>>> >>>> I want to estimate the effects of GDP growth and other macroeconomic variables >>> on bond spreads, so my dependent variable in the main equation is the yield >>> spread of a bond. The problem is that these spreads are primary market spreads >>> or "spreads at launch", which means they are only observed at the moment a >>> country places a bond in the market. >>>> >>>> My panel data are organized at a quarterly frequency. Whether a country issues >>> one or multiple bonds in a given quarter is irrelevant as I basically take a >>> weighted average of all spreads issued in a given quarter and use that as my >>> dependent variable. >>>> >>>> However, there are quarters when a country may not issue a bond... and this is >>> the selection problem I'm trying to get at using a Heckman model. >>>> >>>> On top of this, if we believe that the spreads are somehow related to the >>> level of interest rates in the country, then macroeconomic variables such as GDP >>> growth are going to be endogenous. I have one (potentially two) instrumental >>> variable I want to use, and this is why I want to do the 2SLS... >>>> >>>> Do you guys have any other suggestions besides what I suggested above? > > * > * 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/ _________________________________________________________________ Windows Live™: Keep your life in sync. http://windowslive.com/explore?ocid=PID23384::T:WLMTAGL:ON:WL:en-US:NF_BR_sync:082009 * * 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: Sample selection and endogeneity (or, combining heckman and ivreg)***From:*Austin Nichols <austinnichols@gmail.com>

**References**:**st: Poisson vs. Linear regression for comparing rates***From:*Ashwin Ananthakrishnan <ashwinna@yahoo.com>

**Re: st: Poisson vs. Linear regression for comparing rates***From:*Maarten buis <maartenbuis@yahoo.co.uk>

**st: Sample selection and endogeneity (or, combining heckman and ivreg)***From:*kokootchke <kokootchke@hotmail.com>

**Re: st: Sample selection and endogeneity (or, combining heckman and ivreg)***From:*John Antonakis <john.antonakis@unil.ch>

**Re: st: Sample selection and endogeneity (or, combining heckman and ivreg)***From:*Shehzad Ali <drshehzad_ali@yahoo.com>

**Re: st: Sample selection and endogeneity (or, combining heckman and ivreg)***From:*Austin Nichols <austinnichols@gmail.com>

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