[Date Prev][Date Next][Thread Prev][Thread Next][Date index][Thread index]

From |
"Danny Cohen-Zada" <danoran@bgu.ac.il> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: ivprobit estimation with weak instruments |

Date |
Mon, 10 Mar 2008 17:34:45 +0200 |

It is known that when one uses weak instruments, the standard error of the endogenous regressor is baised.

Suppose for example that i have the following model in which y2 is the endogenous regressor:

1) y1= ao + a1*y2 + a2*x1 (y1 - is a dichotomous variable)

2) y2=b0+b1*x1+b2*z1 (z1 is the excluded instrument0

(one instrument, one endogenous regresssor).

In order to obtain unbaised standard errors (due to the problem of weak instruments) i thought to do the following.

regress y2 x1 z1

predict, ppu

probit y1 ppu z1, cluster(x3) vce(boots)

Am i correct that by applying this procedure i can obtain the correct standard errors of the coef. a1?

In addition, i want to graph the predicted probability as a function of y2 , including in the graph the correct confidence interval (I keep all the other variables are at their mean). I thought to run the following commend after the probit estimation:

prgen ppu , f(30) t(38) rest(mean) gen(pp) gap(1) ci bootstrap

Am i correct that thus i get the correct confidence interval for the predicted probability (even when my instruments are weak)?

Thanks,

Danny

Dr. Danny Cohen-Zada

Department of Economics

Ben-Gurion University of the Negev

P.O.Box 653

Beer-Sheva 84105

Israel

Tel: +972-8-6472301

Fax: +972-8-6472941

http://www.econ.bgu.ac.il/facultym/danoran/main.htm

*

* For searches and help try:

* http://www.stata.com/support/faqs/res/findit.html

* http://www.stata.com/support/statalist/faq

* http://www.ats.ucla.edu/stat/stata/

- Prev by Date:
**st: Cluster analyis on hand made distance matrix** - Next by Date:
**Re: st: simulation of survival datasets in Stata** - Previous by thread:
**st: Cluster analyis on hand made distance matrix** - Next by thread:
**st: storing correlation coefficient** - Index(es):

© Copyright 1996–2015 StataCorp LP | Terms of use | Privacy | Contact us | What's new | Site index |