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From |
"Mike Hollis" <mehla@earthlink.net> |

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

Subject |
st: RE: Test coefficients across equations |

Date |
Fri, 27 Jun 2003 07:53:58 -0700 |

On option I suggested to Borsant was that he consider using software that includes routines explicitly for multiple group analysis. Lisrel, Amos and Mplus (included in the software links on Stata's home page) are among the possibilities. The features in these full information ML estimators include the ability to explicitly estimate and test for a variant of coefficient constraints within and between groups. Correlations for residuals between equations (i.e., groups) can also be estimated, as with Zellner's method. The new piece of information provided by Borsant that causes me to now question the appropriateness of the multi-group strategy is his statement that groups may have transitioned from one to another over time. Allowing the simple correlation of error terms, as in Zellner's method, is unlikely to be an adequate strategy for handling the effects of this type of non-independence. At this point, he may need to consider multi-group hierarchical modeling (features that software like Mplus and Amos) with the higher-order effects essentially accounting for the transition of firms from one group to the next. I've been out of the field for some time, but there was some work involving growth models and the analysis of change that might be helpful in this area. Most of that work was being done in the area of cognitive development and testing. You might take a look through this literature -- or check Bengt Muthen's web page at ULCA (Muthen developed Mplus) -- for possible leads. Another possibility would be to ask this questions of the people involved with structural or hierarchical modeling since they seem to have done the most work in the area of multiple group analysis. -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu]On Behalf Of Bersant Hobdari Sent: Friday, June 27, 2003 2:52 AM To: statalist@hsphsun2.harvard.edu Subject: st: Test coefficients across equations Hi Everyone, Many thanks to Scott Merryman, David Moore and Mike Hollis for their comments on my original message. I however have still some doubts regarding the way I should follow. I will explain it in more detail taking also into account comments of Scott, David and Mike. I am estimating the same specification on different samples and want to test coefficients equality across the samples. The main gist of Scott, Davis and Mike argument was that I introduce ownership dummies and respective interactions in the pooled sample and then apply Chow type tests on individual equations. This however, as they themselves stress, needs sub-samples to be independent. I have serious doubts that my sub-samples are independent. More specifically, I divide the big sample into smaller ones based on majority ownership. Given that ownership changes over time a given firm might be present at different sub-samples over time. I assume this is enough to state that sub-samples are not independent. The reason for sample separation is the endogeneity of ownership structures to the left hand side variable, labor productivity in this case. If I ignore this problem I will be in a bigger problem that the one I am trying to solve. Given non-independence then what is the way to test coefficient equality across equations. One suggestion would be to use Zellner's SUR method, suggested by Scott. To my knowledge however SUR estimates equation by equation OLS accounting for cross equation correlation. I however have used GMM (through ivreg2 procedure) to obtain estimates. Can SUR be used with GMM? The big question then becomes: how do I test coefficients equality across equations estimated on different samples when samples are not independent? Any help is highly appreciated. Sincerely, Bersant Hobdari Content-Type: multipart/alternative; boundary="--=a921961f-c433-46a5-840e-89a84a4a191d" ----=a921961f-c433-46a5-840e-89a84a4a191d Content-Type: text/plain Content-Transfer-Encoding: 7bit **************************************************************************** Denne e-mail er scannet af mailFence fra Sure Solutions (www.suresolutions.dk), og der er ikke fundet vira. **************************************************************************** ----=a921961f-c433-46a5-840e-89a84a4a191d Content-Type: text/html Content-Transfer-Encoding: quoted-printable <HTML><HEAD> </HEAD><BODY>=20 <HR> <DIV align=3Dcenter><FONT face=3DArial size=3D1>Denne e-mail er scannet a= f mailFence=20 fra Sure Solutions (</FONT><A href=3D"http://www.suresolutions.dk";><FONT = face=3DArial size=3D1>www.suresolutions.dk</FONT></A><FONT face=3DArial s= ize=3D1>), og=20 der er ikke fundet vira.</FONT></DIV> <DIV> <HR> </DIV> </BODY></HTML> ----=a921961f-c433-46a5-840e-89a84a4a191d-- * * 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/

**References**:**st: Test coefficients across equations***From:*Bersant Hobdari <bh.cees@cbs.dk>

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