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

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Interesting Results - But Am I Right? |

Date |
Sun, 26 Apr 2009 08:07:36 -0400 |

Sachin Chintawar <schint1@tigers.lsu.edu>: Probably you are greatly increasing the strength of the instruments as you increase the number of instruments--you can check the first-stage stats with e.g. -ranktest- on SSC (see also -ivreg2- on SSC for context), or derive analytically the concentration parameter or equivalent (see e.g. http://ksghome.harvard.edu/~jstock/ams/websupp/rfa_7.pdf and related material). A more natural model is one where the additional instruments do not have substantial additional explanatory power for the endog var, i.e. you have 4 essentially identical instruments differing from each other only via some noise, any one of which would be a mediocre instrument, and putting all 4 in actually is worse than just using one. On Fri, Apr 24, 2009 at 5:00 PM, Sachin Chintawar <schint1@tigers.lsu.edu> wrote: > Dear Statalist Users > I have been playing around with endogenous variable models and the > hypothsis that 'An increase in instruments tend to increase the bias > of our estimates'. While this was shown to be true by A. Buse 'The > Bias of Instrumental Variable Estimators' in Econometrica (1992). My > simulation results showed the contrary (A simple variation was that > this was a probit model - Thanks to Mr. Martin for the million > questions while I was coding it). The program until now is given > below. Under the conditions specified I see that as I increase the > instuments (from z1 to z4) the bias in the 'beta' value actually > decreases. My question is > 1. Am I specifying everything in the model right? > 2. Why this difference in results from another paper? * * 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: Interesting Results - But Am I Right?***From:*Sachin Chintawar <schint1@tigers.lsu.edu>

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