Stata The Stata listserver
[Date Prev][Date Next][Thread Prev][Thread Next][Date index][Thread index]

Re: st: xtabond2 problem


From   "Mark Schaffer" <M.E.Schaffer@hw.ac.uk>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: xtabond2 problem
Date   Wed, 13 Oct 2004 16:27:29 +0100

Socrates,

My guess is the key is your Question 3.  These variables are all 
prefixed with "d".  Are they dummies?  If so, it's easy to see how 
first-differencing would wipe a lot of them out.  Solve this and 
you'll probably solve Q2 as well.  Regarding Q1, lots of instruments 
relative to the number of observations can generate severe finite-
sample bias problems.  It's nice that -xtabond2- alerts you to this; 
it's a potentially serious problem that many researchers aren't aware 
of.

--Mark

From:           	Socrates Mokkas <socrates.mokkas@st-antonys.oxford.ac.uk>
Date sent:      	Wed, 13 Oct 2004 13:23:25 +0100 (BST)
To:             	statalist@hsphsun2.harvard.edu
Subject:        	st: xtabond2 problem
Send reply to:  	statalist@hsphsun2.harvard.edu

> Hi there,
> 
> I am trying to estimate a model with xtabond2 and I keep coming up with serious problems.
> Below is the output of my effort.
> 
> Question No1: Why is it warning me that instruments are large relative to number of observations and how can I reduce the instruments. The only variable that I want to instrument is the lag of the dependent variable.
> 
> Question No2: Why is the covariance matrix of moment conditions singular? How can I get that right?
> 
> Question No3: Why is it dropping almost all the variables? I know that they are not multicollinear!
> 
> Thanks very much for your help,
> 
> Socrates
> 
> . xtabond2  ca L.ca dsolpr dsol dsolaft dwolpr dwol dwolaft dwcpr dwc dwcaft d1-d131, gmmstyle(L.ca, lag(1 2)) twostep robust
> d1 dropped because of collinearity.
> Building GMM instruments..
> Warning: Number of instruments may be large relative to number of observations.
> Estimating.
> Warning: Two-step estimated covariance matrix of moment conditions is singular.
> Number of instruments may be large relative to number of groups.
> Using a generalized inverse to calculate optimal weighting matrix for two-step estimatio
> > n.
> Computing Windmeijer finite-sample correction...........
> Performing specification tests.
> 
> Arellano-Bond dynamic panel-data estimation, two-step system GMM results
> ------------------------------------------------------------------------------
> Group variable: cntr                            Number of obs      =      1169
> Time variable : t                               Number of groups   =        10
> Number of instruments = 390                     Obs per group: min =        87
> F(140, 9)     =      0.08                                      avg =    116.90
> Prob > F      =     1.000                                      max =       131
> ------------------------------------------------------------------------------
>              |              Corrected
>              |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
> -------------+----------------------------------------------------------------
> ca           |
>           L1 |  (dropped)
> dsolpr       |   .0456957   .1109821     0.41   0.690    -.2053633    .2967546
> dsol         |  (dropped)
> dsolaft      |  (dropped)
> dwolpr       |  (dropped)
> dwol         |  (dropped)
> dwolaft      |   .0516802   .6528166     0.08   0.939    -1.425094    1.528454
> dwcpr        |  (dropped)
> dwc          |  (dropped)
> dwcaft       |  -.3606597   1.910496    -0.19   0.854    -4.682502    3.961182
> d2           |  (dropped)
> d3           |  (dropped)
> d4           |  (dropped)
> d5           |  (dropped)
> d6           |  (dropped)
> d7           |  (dropped)
> d8           |  (dropped)
> d9           |  (dropped)
> d10          |  (dropped)
> d11          |  (dropped)
> d12          |  (dropped)
> d13          |  (dropped)
> d14          |  (dropped)
> d15          |  (dropped)
> d16          |  (dropped)
> d17          |  (dropped)
> d18          |  (dropped)
> d19          |  (dropped)
> d20          |  (dropped)
> d21          |  (dropped)
> d22          |    .004763   .0807997     0.06   0.954    -.1780188    .1875447
> d23          |   .0389608   .0370386     1.05   0.320    -.0448263    .1227479
> d24          |  (dropped)
> d25          |  (dropped)
> d26          |  (dropped)
> d27          |  (dropped)
> d28          |  (dropped)
> d29          |  (dropped)
> d30          |  (dropped)
> d31          |  (dropped)
> d32          |   .0040198   .0365386     0.11   0.915    -.0786363     .086676
> d33          |  (dropped)
> d34          |  (dropped)
> d35          |  (dropped)
> d36          |  (dropped)
> d37          |  (dropped)
> d38          |  (dropped)
> d39          |  (dropped)
> d40          |  (dropped)
> d41          |  (dropped)
> d42          |  (dropped)
> d43          |  (dropped)
> d44          |  (dropped)
> d45          |  (dropped)
> d46          |  (dropped)
> d47          |  (dropped)
> d48          |  (dropped)
> d49          |  (dropped)
> d50          |  (dropped)
> d51          |  (dropped)
> d52          |  (dropped)
> d53          |  (dropped)
> d54          |  (dropped)
> d55          |  (dropped)
> d56          |  (dropped)
> d57          |  (dropped)
> d58          |  (dropped)
> d59          |  (dropped)
> d60          |  (dropped)
> d61          |  (dropped)
> d62          |  (dropped)
> d63          |  (dropped)
> d64          |  (dropped)
> d65          |  (dropped)
> d66          |  (dropped)
> d67          |  (dropped)
> d68          |  (dropped)
> d69          |  (dropped)
> d70          |  (dropped)
> d71          |  (dropped)
> d72          |  (dropped)
> d73          |  (dropped)
> d74          |  (dropped)
> d75          |  (dropped)
> d76          |  (dropped)
> d77          |  (dropped)
> d78          |  (dropped)
> d79          |  (dropped)
> d80          |  (dropped)
> d81          |  (dropped)
> d82          |  (dropped)
> d83          |  (dropped)
> d84          |  (dropped)
> d85          |  (dropped)
> d86          |  (dropped)
> d87          |  (dropped)
> d88          |  (dropped)
> d89          |  (dropped)
> d90          |  (dropped)
> d91          |  (dropped)
> d92          |  (dropped)
> d93          |  (dropped)
> d94          |  (dropped)
> d95          |  (dropped)
> d96          |  (dropped)
> d97          |  (dropped)
> d98          |  (dropped)
> d99          |  (dropped)
> d100         |  (dropped)
> d101         |  (dropped)
> d102         |  (dropped)
> d103         |  (dropped)
> d104         |  (dropped)
> d105         |  (dropped)
> d106         |  (dropped)
> d107         |  (dropped)
> d108         |  (dropped)
> d109         |  (dropped)
> d110         |  (dropped)
> d111         |   .9831839   3.246474     0.30   0.769    -6.360851    8.327219
> d112         |   .7838466   3.484041     0.22   0.827    -7.097601    8.665295
> d113         |  (dropped)
> d114         |  -.0019199   .3928971    -0.00   0.996    -.8907149     .886875
> d115         |  (dropped)
> d116         |  (dropped)
> d117         |  (dropped)
> d118         |  (dropped)
> d119         |  (dropped)
> d120         |  (dropped)
> d121         |  (dropped)
> d122         |  (dropped)
> d123         |  (dropped)
> d124         |  (dropped)
> d125         |  (dropped)
> d126         |  (dropped)
> d127         |  (dropped)
> d128         |  (dropped)
> d129         |  (dropped)
> d130         |  (dropped)
> d131         |  (dropped)
> _cons        |   .0095233   .1761511     0.05   0.958    -.3889581    .4080047
> ------------------------------------------------------------------------------
> Hansen test of overid. restrictions: chi2(249) =    0.00  Prob > chi2 =  1.000
> 
> Arellano-Bond test for AR(1) in first differences: z =  -0.06  Pr > z =  0.949
> Arellano-Bond test for AR(2) in first differences: z =  -0.23  Pr > z =  0.814
> ------------------------------------------------------------------------------
> *
> *   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/

Prof. Mark E. Schaffer
Director
Centre for Economic Reform and Transformation
Department of Economics
School of Management & Languages
Heriot-Watt University, Edinburgh EH14 4AS  UK
44-131-451-3494 direct
44-131-451-3008 fax
44-131-451-3485 CERT administrator
http://www.som.hw.ac.uk/cert

*
*   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/



© Copyright 1996–2014 StataCorp LP   |   Terms of use   |   Privacy   |   Contact us   |   What's new   |   Site index