Re: st: A layman question on model building

[John Antonakis <John.Antonakis@unil.ch>]

Sorry....a small clarification (based on off of-line question I got). By 
"eq. 2-5c", I meant to say, see Equations 2-5c, which show that 
consistency is not harmed by including an omitted nonsignificant regressor.

Best,
J.

__________________________________________

John Antonakis
Professor of Organizational Behavior
Director, Ph.D. Program in Management

Faculty of Business and Economics
University of Lausanne
Internef #618
CH-1015 Lausanne-Dorigny
Switzerland
Tel ++41 (0)21 692-3438
Fax ++41 (0)21 692-3305
http://www.hec.unil.ch/people/jantonakis

Associate Editor
The Leadership Quarterly
__________________________________________

On 07.03.2013 08:22, John Antonakis wrote:
> Hi:
>
> If you have a sufficiently large sample size and the regressors of 
> interest are significant predictors, then it is best to leave in the 
> controls; they do not harm but help consistency (even if only a tad). 
> What suffers is efficiency (standard errors) and this is amplified in 
> small sample size conditions. I would (mostly) always err on the side 
> of caution and include the controls. A couple of things to do before 
> considering dropping are: (a) to do a Wald test to test whether the 
> controls are simultaneously different from zero; (b) to do a Hausman 
> test comparing the consistent and efficient estimator or a Chow test 
> for the common regressors. See the first series of discussions (eq. 
> 2-5c to see that consistency is never harmed even if a omitted 
> regressor is not a significant predictor: Antonakis, J., Bendahan, S., 
> Jacquart, P., & Lalive, R. 2010. On making causal claims: A review and 
> recommendations. The Leadership Quarterly, 21(6): 1086-1120. 
> http://www.hec.unil.ch/jantonakis/Causal_Claims.pdf
>
> Best,
> J.
>
> __________________________________________
>
> John Antonakis
> Professor of Organizational Behavior
> Director, Ph.D. Program in Management
>
> Faculty of Business and Economics
> University of Lausanne
> Internef #618
> CH-1015 Lausanne-Dorigny
> Switzerland
> Tel ++41 (0)21 692-3438
> Fax ++41 (0)21 692-3305
> http://www.hec.unil.ch/people/jantonakis
>
> Associate Editor
> The Leadership Quarterly
> __________________________________________
>
> On 07.03.2013 08:07, James Bernard wrote:
> > Hi all,
> >
> > I have a question which may sound too basic, but I wonder if anyone 
> > could help:
> >
> > We often add control variables that turn out to be insignificant. Does
> > that mean that I can remove that variable form my model without being
> > concerned with omitted variable bias?
> >
> > Thanks,
> > James
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