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Re: st: xtabond2 - Post estimation interpretation

From   Murod Aliyev <>
To   "" <>
Subject   Re: st: xtabond2 - Post estimation interpretation
Date   Tue, 29 Jan 2013 11:21:49 +0000 (GMT)

Dear Davide

1) I think this depends on the context of your work, and on the specification of your model. As far as it concerns xtabond2, you can include any variable.

2) You are right with your AR test results. Usually you expect AR(1) in differences to be present, and this is fine for the estimation method. You should mainly look at AR(2) in differences which is important, there should be no AR(2). If there is, you should go deeper and deeper with lags when specifying gmm instrument set.
I think Sargan/Hansen test is instrument validity test, which means they test exogeneity of instruments, not their relevance (weakness/strength).

Hope this helps.

Best wishes,

From: Davide Mare <>
Sent: Monday, 28 January 2013, 18:10
Subject: st: xtabond2 - Post estimation interpretation

Dear all,

I am struggling to interpret the results I get after using the
xtabond2 command. I have two main questions:

1) Does it make sense to use macroeconomics variables in a cross
country regression explicitly in the specification before the comma
(e.g. unemployment to control for the possible effect of labour
2) I am not sure on the interpretation of the results I get from the
model I am implementing, specifically on the validity of the
instruments. Find below the main statistics:

Arellano-Bond test for AR(1) in first differences: z =  -1.67  Pr > z =  0.095
Arellano-Bond test for AR(2) in first differences: z =  0.11  Pr > z =  0.916

Sargan test of overid. restrictions: chi2(98)  = 289.36  Prob > chi2 =  0.000
Hansen test of overid. restrictions: chi2(98)  = 188.54  Prob > chi2 =  0.000

Difference-in-Hansen tests of exogeneity of instrument subsets:
Hansen test excluding group:    chi2(88)  = 173.65  Prob > chi2 =  0.000
Difference (null H = exogenous): chi2(10)  =  14.90  Prob > chi2 =  0.136

If my understanding is correct, I have no serial correlation in the
first order errors, second-order GMM residual serial correlation and
the estimation fails to satisfy the Sargan/Hansen test statistics of
overidentifying restrictions. Hence, the instrumental variables I am
using in the estimation are weak.

Thank you in advance for your help.

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