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From |
Austin Nichols <austinnichols@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Standard Error of a Wald Estimator and -nlcom- |

Date |
Thu, 15 Oct 2009 15:33:02 -0400 |

Misha Spisok <misha.spisok@gmail.com> : The Wald estimator with the correct standard error is here: use http://pped.org/card.dta ivreg lwage exper (educ=nearc4), nohe r as shown in http://www.stata.com/statalist/archive/2009-10/msg00498.html You can also: reg lwage exper nearc4, nohe r loc b1=_b[nearc4] loc s1=_se[nearc4] reg educ exper nearc4, nohe r loc b2=_b[nearc4] loc s2=_se[nearc4] di `b1'/`b2' and use -suest- and so forth, but why would you? Unless you are estimating on two separate datasets... On Thu, Oct 15, 2009 at 3:19 PM, Misha Spisok <misha.spisok@gmail.com> wrote: > Prof. Nichols, > > Please forgive my obtuseness, but I'm not sure what you mean by > "rather than aggregating quantities over multiple regressions." I > think you are referring to using the results from separate regressions > on the same data set, as you point out in the first line of the post > to which you referred me. Please correct me if I'm wrong. > > Also, by having "three ways to get a SE," do you mean to include the > initial one from the code > (http://www.stata.com/statalist/archive/2009-10/msg00498.html) that > comes from the two separate OLS regressions and the following > calculation? > > di `b1'/`b2'*sqrt((`s2'/`b2')^2+(`s1'/`b1')^2) > > I would understand this to be incorrect for the reasons given in the > first line of the referenced post--i.e., it uses the results from > separate estimates on the same data--in addition to the fact that it > neglects to correct for any correlation between b1 and b2. > > And, for the sake of clarity, the other two being: > > di `b1'/`b2'*sqrt((`s2'/`b2')^2+(`s1'/`b1')^2-2*`c'/`b1'/`b2') > > which, I understand to be an approximate standard error formula with a > correction for non-zero covariance, and > > nlcom [r1_mean]_b[nearc4]/[r2_mean]_b[nearc4] > > which, if I understand the documentation correctly, uses some > numerical implementation of the delta method. > > Thank you for your time and patience. I appreciate you correcting my > misunderstandings and taking the time to provide tidy examples. > > Best, > > Misha > > On Thu, Oct 15, 2009 at 8:49 AM, Austin Nichols <austinnichols@gmail.com> wrote: >> Misha Spisok <misha.spisok@gmail.com> : >> Instead of focusing on the final line, look at the first sentence of the post: >> http://www.stata.com/statalist/archive/2009-10/msg00498.html >> You have 3 ways to get a SE, not 2, and -ivreg- or equivalent (I use >> -ivreg2- from SSC) is the way to go, rather than aggregating >> quantities over multiple regressions. >> >> On Wed, Oct 14, 2009 at 8:58 PM, Misha Spisok <misha.spisok@gmail.com> wrote: >>> In brief, are the two following approaches for the standard error of a >>> Wald estimate equivalent? If not, why not? >>> >>> use http://pped.org/card.dta >>> reg lwage exper nearc4, nohe r >>> loc b1=_b[nearc4] >>> loc s1=_se[nearc4] >>> reg educ exper nearc4, nohe r >>> loc b2=_b[nearc4] >>> loc s2=_se[nearc4] >>> ivreg lwage exper (educ=nearc4), nohe r >>> di `b1'/`b2' >>> di `b1'/`b2'*sqrt((`s2'/`b2')^2+(`s1'/`b1')^2) >>> >>> qui reg lwage exper nearc4 >>> est sto r1 >>> qui reg educ exper nearc4, nohe >>> est sto r2 >>> suest r1 r2 >>> mat v=e(V) >>> matrix cov=v["r1_mean:nearc4","r2_mean:nearc4"] >>> loc c=cov[1,1] >>> >>> >>> -----Approach 1----- >>> >>> di `b1'/`b2'*sqrt((`s2'/`b2')^2+(`s1'/`b1')^2-2*`c'/`b1'/`b2') >>> >>> This final line is the result of the approach suggested by Austin >>> Nichols (http://www.stata.com/statalist/archive/2009-10/msg00498.html) >>> to get the standard error for the Wald estimator. >>> >>> Then, using the above results from -suest-, >>> >>> -----Approach 2----- >>> >>> nlcom [r1_mean]_b[nearc4]/[r2_mean]_b[nearc4] >>> >>> The results for the standard error are close (the difference is >>> 0.00001913), but not exactly the same. Are the two approaches >>> analytically equivalent but different only numerically? >>> >>> Thank you for your time and attention. >>> >>> Misha * * 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/

**References**:**st: Standard Error of a Wald Estimator and -nlcom-***From:*Misha Spisok <misha.spisok@gmail.com>

**Re: st: Standard Error of a Wald Estimator and -nlcom-***From:*Austin Nichols <austinnichols@gmail.com>

**Re: st: Standard Error of a Wald Estimator and -nlcom-***From:*Misha Spisok <misha.spisok@gmail.com>

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