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From |
Bert Lloyd <bert.lloyd.89@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: computing elasticities after using lpoly |

Date |
Sun, 28 Oct 2012 21:51:55 -0400 |

Dear Austin, Sorry to be imprecise and thanks for allowing me to revise-and-resubmit. My question is about inference on the estimated slope, rather than the estimated conditional mean. In terms of your example, are the standard errors given by _se[time] likely to be consistent? If not, is there a way to obtain the analytical standard errors for the slope term directly from lpoly? Or would a bootstrapping approach be preferable? (If I am reading the help file for R's np package correctly, npreg and related functions compute analytical standard errors for the gradient but also provide bootstrap estimates -- see citation below.) Thanks, BL Hayfield and Racine, "The np package," v 0.40-13, 2012; pages 9-11. http://cran.r-project.org/web/packages/np/vignettes/np.pdf Li and Racine, Nonparametric Econometrics, 2007, provide a formula for the asymptotic variance of the local polynomial estimator (Theorem 2.10, pg. 90), although it is not obvious to me whether this is for data assumed to be i.i.d. (homoskedastic) or i.n.i.d. (heteroskedastic). On Sun, Oct 28, 2012 at 7:11 PM, Austin Nichols <austinnichols@gmail.com> wrote: > Bert Lloyd <bert.lloyd.89@gmail.com>: > 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 <bert.lloyd.89@gmail.com> 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 >> * * 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/

**Follow-Ups**:**Re: st: computing elasticities after using lpoly***From:*Austin Nichols <austinnichols@gmail.com>

**References**:**st: computing elasticities after using lpoly***From:*Arka Roy Chaudhuri <gabuisi@gmail.com>

**Re: st: computing elasticities after using lpoly***From:*Nick Cox <njcoxstata@gmail.com>

**Re: st: computing elasticities after using lpoly***From:*Arka Roy Chaudhuri <gabuisi@gmail.com>

**Re: st: computing elasticities after using lpoly***From:*Nick Cox <njcoxstata@gmail.com>

**Re: st: computing elasticities after using lpoly***From:*Maarten Buis <maartenlbuis@gmail.com>

**Re: st: computing elasticities after using lpoly***From:*Nick Cox <njcoxstata@gmail.com>

**Re: st: computing elasticities after using lpoly***From:*Arka Roy Chaudhuri <gabuisi@gmail.com>

**Re: st: computing elasticities after using lpoly***From:*Austin Nichols <austinnichols@gmail.com>

**Re: st: computing elasticities after using lpoly***From:*Austin Nichols <austinnichols@gmail.com>

**Re: st: computing elasticities after using lpoly***From:*Bert Lloyd <bert.lloyd.89@gmail.com>

**Re: st: computing elasticities after using lpoly***From:*Austin Nichols <austinnichols@gmail.com>

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