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Re: st: computing elasticities after using lpoly
From
Austin Nichols <[email protected]>
To
[email protected]
Subject
Re: st: computing elasticities after using lpoly
Date
Sun, 28 Oct 2012 19:11:06 -0400
Bert Lloyd <[email protected]>:
I do not understand your question; are you asking whether -lpoly-
computes consistent standard errors? If so, please read the manual
entry for -lpoly- and the references therein. If you mean CIs in my
example, there are none!
On Sat, Oct 27, 2012 at 10:43 PM, Bert Lloyd <[email protected]> wrote:
> Dear Austin,
>
> This looks like a very clever solution. Do you have a sense of whether
> the confidence intervals are likely to be consistent? If not, would
> you recommend a bootstrapping approach?
>
> Thanks,
> BL
>
> On Tue, Oct 9, 2012 at 11:53 AM, Austin Nichols <[email protected]> wrote:
>> Arka Roy Chaudhuri <[email protected]>:
>> For a worked example, try:
>>
>> webuse motorcycle, clear
>> lpoly accel time, deg(1) k(tri) bw(3) gen(x s)
>> qui levelsof x, loc(xs)
>> g double schk=.
>> g double b=.
>> loc i 1
>> qui foreach l of loc xs {
>> gen double w=max(0,3-abs(time-`l'))
>> reg accel time [aw=w]
>> replace schk=_b[_cons]+_b[time]*`l' in `i'
>> replace b=_b[time] in `i'
>> drop w
>> loc i=`i'+1
>> }
>> assert float(s)==float(schk)
>> la var b "Slope"
>> la var s "Conditional mean"
>> sc s b x, msize(small small) c(l) name(slopes)
>>
>>
>> On Tue, Oct 9, 2012 at 10:56 AM, Austin Nichols <[email protected]> wrote:
>>> Arka Roy Chaudhuri <[email protected]>:
>>> You can also get the coefs from an -lpoly- graph by noting the kernel
>>> type, bandwidth, and degree, then estimating the weighted regressions
>>> yourself, saving the coefs each time. If you specify the -generate(x
>>> s)- option you can also get all the X points at which regressions are
>>> estimated.
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