Re: st: RE: Re: Marginal effects after ivreg2

[Suyin Chang <suyinlchang@gmail.com>]

Deark Mark,

Both points taken. First, thinking a bit more about it, I tend to
agree that nothing has to be done differently with the interactions
fitted with the clustered SEs. It would make more sense to think of a
more meaningful way of presenting the interaction in a full
multi-level modelling, but only with the clustered SEs your general
solution mentioned initially seems to be quite enough.

Second, you are absolutely right on the suggestion that I should have
started a new thread. My mistake. I will forward this to a new one,
asking for any solution to plot the conditional effects extracted
directly with nlcom.

Thanks again for your thoughts.

Suyin

2014/1/15 Schaffer, Mark E <M.E.Schaffer@hw.ac.uk>:
> Suyin,
>
>> -----Original Message-----
>> From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-
>> statalist@hsphsun2.harvard.edu] On Behalf Of Suyin Chang
>> Sent: 15 January 2014 10:02
>> To: statalist@hsphsun2.harvard.edu
>> Subject: Re: st: RE: Re: Marginal effects after ivreg2
>>
>> Dear Mark,
>>
>> This was quite helpful. I was trying something very similar, but making a silly
>> mistake in how to call the values generated in the loop. Thanks for the lines of
>> code.
>> While we wait to see if there will be any suggestions coming from the list
>> regarding how to plot those values, I would like to bring you still another
>> follow-up question to push forward these workarounds. As we are here talking
>> about how to make marginal effects available to
>> -ivreg2- while it does not integrate directly with -margins-, one question comes
>> to my mind: what about clustered se?
>>
>> One of the main reasons I frequently to 2sls in Stata (besides trying to isolate
>> misspecification errors in individual equations when I run nonrecursive
>> models), is its much greater flexibility than the 3sls estimation from -reg3-
>> regarding the the standard errors, e.g. the robust and cluster possibilities.
>> Therefore, when we use cluster se in the 2sls estimation through cluster(var) as
>> an option, what would be your suggestion on how to present meaningful
>> marginal effects for interaction terms?
>
> Cluster-robust SEs just affect the SEs.  -nlcom- doesn't care where the VCE comes from.  If it's cluster-robust, then the marginal effects will be cluster-robust.  So I don't see what the issue is.
>
> Cheers,
> Mark
>
> NB:   My other suggestion is to use a new subject heading when starting a new thread, as per the Statalist FAQ. :o)
>
>>
>> Thanks for your insights.
>>
>> Suyin
>>
>> 2014/1/14 Schaffer, Mark E <M.E.Schaffer@hw.ac.uk>:
>> > Suyin,
>> >
>> >> -----Original Message-----
>> >> From: Suyin Chang [mailto:suyinlchang@gmail.com]
>> >> Sent: 14 January 2014 06:19
>> >> To: statalist@hsphsun2.harvard.edu; Schaffer, Mark E
>> >> Subject: Re: st: RE: Re: Marginal effects after ivreg2
>> >>
>> >> Dears Jana and Mark,
>> >>
>> >> Very interesting question, followed by a promising reply.
>> >> However, I would like to ask two quick follow-up questions, if I may.
>> >>
>> >> The first problem is I don't get how to mimic -margins- with -nlcom-
>> >> after
>> >> ivreg2 in case we want a linear plot. For instance, how to mimic
>> >> something like margins, dydx(mgp) at(turn=(start(by)end)), where
>> >> start is the first value and end is the last value of the variable
>> >> turn to be considered? That appears to me as something less intuitive to
>> achieve.
>> >
>> > This is also easy to do - all you need to do is loop through the values and apply
>> -nlcom- each time.  Here is a modified version of my original example with -
>> regress-:
>> >
>> > sysuse auto, clear
>> > gen mpgturn=mpg*turn
>> >
>> > regress price mpg turn mpgturn
>> > forvalues x=31(1)51 {
>> >         nlcom _b[mpg] + _b[mpgturn]*(`x') }
>> >
>> > regress price mpg turn c.mpg#c.turn
>> > margins, dydx(mpg) at(turn=(31(1)51))
>> >
>> >> And the second thing is to ask if there is a way to easily plot those
>> >> results such as marginsplot does with margins saved output.
>> >
>> > Maybe someone else has some suggestions here...?
>> >
>> > --Mark
>> >
>> >
>> >> Any suggestions would be very much appreciated, as I am facing the
>> >> same need as Jana in the original question, i.e. I need to generate a
>> >> marginal effects plot for an interaction between the endogenous
>> >> explanatory variable and a exogenous explanatory variable (both
>> continuous).
>> >>
>> >> Thanks,
>> >>
>> >> Suyin
>> >>
>> >>
>> >>
>> >>
>> >>
>> >> 2013/12/26 Schaffer, Mark E <M.E.Schaffer@hw.ac.uk>:
>> >> > Jana,
>> >> >
>> >> > -ivreg2- doesn't (yet - we really need to add this in!) support
>> >> > -margins-.  But
>> >> an easy workaround is to use -nlcom- with -ivreg2-.
>> >> >
>> >> > Below is an example of how to use -nlcom- to mimic -margins- to
>> >> > calculate
>> >> marginal effects and CIs when you have an interaction.
>> >> >
>> >> > HTH,
>> >> > Mark
>> >> >
>> >> > sysuse auto, clear
>> >> > gen mpgturn=mpg*turn
>> >> > regress price mpg turn mpgturn
>> >> > qui sum turn, meanonly
>> >> > nlcom _b[mpg] + _b[mpgturn]*(`r(mean)') qui sum mpg, meanonly nlcom
>> >> > _b[turn] + _b[mpgturn]*(`r(mean)') regress price mpg turn
>> >> > c.mpg#c.turn margins, atmeans dydx(*)
>> >> >
>> >> >> -----Original Message-----
>> >> >> From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-
>> >> >> statalist@hsphsun2.harvard.edu] On Behalf Of Jana von Stein
>> >> >> Sent: 26 December 2013 01:59
>> >> >> To: <statalist@hsphsun2.harvard.edu>
>> >> >> Subject: st: Re: Marginal effects after ivreg2
>> >> >>
>> >> >> Hello,
>> >> >>
>> >> >> I need to run margins (or calculate marginal effects with ci's)
>> >> >> after ivreg2. I have an endogenous interaction and want to
>> >> >> calculate the marginal effect (w/
>> >> >> ci's) after ivreg2. Does anyone know how to do this? Margins did
>> >> >> not seem to work after ivreg2.
>> >> >>
>> >> >> Thanks, and happy holidays.
>> >> >> Jana
>> >> >>
>> >> >>
>> >> >>
>> >> >>
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> -----
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> Fourth university in the UK and top in Scotland (National Student Survey 2012)
>
> We invite research leaders and ambitious early career researchers to
> join us in leading and driving research in key inter-disciplinary themes.
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> to apply.
>
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> registered under charity number SC000278.
>
>
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