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From |
sjsamuels@gmail.com |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Iv reg estimates are too large in stnd errors |

Date |
Fri, 20 Nov 2009 10:35:31 -0500 |

I think that Shruti is trying to emulate the analysis in Angrist and Evans, 1998, which saw much larger effects of morethan2children. -Steve Reference: #Children and Their Parents' Labor Supply: Evidence from Exogenous Variation in Family Size # Joshua D. Angrist and William N. Evans # The American Economic Review, Vol. 88, No. 3 (Jun., 1998), pp. 450-477 On Fri, Nov 20, 2009 at 10:08 AM, Austin Nichols <austinnichols@gmail.com> wrote: > I second Maarten: the large SE reflects the large variance inherent in > IV. Note that http://papers.nber.org/papers/w10281 indicates the > effect of sex mix on subsequent fertility is about .02 to .04 so you > will not be using a lot of the variation in your endog var. > > However: note two other points--if you have survey data, you should > not use [aw= but instead [pw= and you should cluster to get more > correct SEs. > Also, you have a binary RHS endog var and binary outcome so you may > prefer another estimator, e.g. -biprobit- or -cmp- (on SSC). > > Also, why not consider boyfirst an excluded instrument? Is the worry > that some families who observe the sex before birth choose not to have > a girl first? > > On Fri, Nov 20, 2009 at 8:13 AM, Maarten buis <maartenbuis@yahoo.co.uk> wrote: >> --- On Fri, 20/11/09, Shruti Kapoor wrote: >>> I am using ivreg for the first time and am not sure if i >>> can do anything to improve my results. The biggest problem >>> i am facing is that the stnd errors on my endogenous variable >>> (morethan2children, even when instrumented) is quite high. >>> Which makes them insignificant. >> >> In general, large standard errors are not a problem, they are >> a finding. We may or may not like that finding, but that is >> irrelevant. >> >> Specifically with instrumental variables, I am not surprised >> that you find large standard errors. Instrumental variables can >> potentially provide you with a very strong argument that the >> effect you found is likely to be causal, but there is always a >> price to be paid: in the case of instrumental variable the >> price is low power (i.e. large standard errors). As the >> economists say: there is no such thing as a free lunch. >> >> -- Maarten > * > * 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/ > -- Steven Samuels sjsamuels@gmail.com 18 Cantine's Island Saugerties NY 12477 USA 845-246-0774 * * 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: Iv reg estimates are too large in stnd errors***From:*Austin Nichols <austinnichols@gmail.com>

**References**:**st: Iv reg estimates are too large in stnd errors***From:*Shruti Kapoor <kapoor@oxy.edu>

**Re: st: Iv reg estimates are too large in stnd errors***From:*Maarten buis <maartenbuis@yahoo.co.uk>

**Re: st: Iv reg estimates are too large in stnd errors***From:*Austin Nichols <austinnichols@gmail.com>

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