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RE: st: coefficient interpretation in OLS

From   "Lynn Lee" <>
To   <>
Subject   RE: st: coefficient interpretation in OLS
Date   Fri, 17 Aug 2012 21:47:41 -0700

Hello Prof. Antonakis,

I read through the part of paper you pointed out to me. The ides is really
clear and very helpful. I appreciate for your suggestion. 

Best Regards,
Lynn Lee

-----Original Message-----
[] On Behalf Of John Antonakis
Sent: Friday, August 17, 2012 2:18 AM
Subject: Re: st: coefficient interpretation in OLS

Hi Lynn:

If you want formal (and simple) explanation run through Eq. 2 to 5c in:

Antonakis, J., Bendahan, S., Jacquart, P., & Lalive, R. (2010). On 
making causal claims: A review and recommendations. The Leadership 
Quarterly, 21(6), 1086-1120.



Prof. John Antonakis
Faculty of Business and Economics
Department of Organizational Behavior
University of Lausanne
Internef #618
CH-1015 Lausanne-Dorigny
Tel ++41 (0)21 692-3438
Fax ++41 (0)21 692-3305

Associate Editor
The Leadership Quarterly

On 17.08.2012 11:06, Nick Cox wrote:
> This really is covered in every decent regression text (in your case,
> perhaps, an econometrics text). It's an inevitable consequence of any
> correlations between X4 and X1, X2, X3.
> Nick
> On Fri, Aug 17, 2012 at 11:25 PM, Lynn Lee <> wrote:
>> When I run simple OLS regression or pooled OLS regression, I find if I
>> more variables to the model, the coefficient on specific explanatory
>> variable can vary in magnitude. For example,
>> Y1=beta+beta1*X1+beta2*X2+beta3*X3+error term;
>> Y2=alpha+alpha1*X1+ alpha2*X2+ alpha3*X3+ alpha4*X4+error term.
>> The absolute value of estimates of beta1 or alpha1 can increase or
>> decrease.  I am not confident to explain this theoretically. Is it
>> to potential endogeneity issue?
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