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st: Jackknife and standard error in NEGBIN model


From   Marc Philipp <marcphilipp@ymail.com>
To   statalist@hsphsun2.harvard.edu
Subject   st: Jackknife and standard error in NEGBIN model
Date   Mon, 4 May 2009 19:17:18 -0700 (PDT)


Dear Stata users,

I have a problem with the jackknife command. Hopefully there are some experienced users who will be able to help me. I am estimating a negative binomial model (NEGBIN 1), regressing a count variable y on a continuous variable x and on some other control variables z1, z2, ... 

Since I am only interested in the parameter of x and in the overdispersion parameter delta, I specified the command in this way:

jackknife _b[x] e(delta), cluster(t): nbreg y x z*, dispersion(constant) nocons

However, I observed that if I specify the command in this way, without collecting the two parameters I am interested in:

jackknife, cluster(tt): nbreg y x z*, dispersion(constant) nocons,

something strange happens: the estimated parameters are exactly the same, but the jackknife standard error of delta is completely different, much higher than in the previous case, whereas the jackknife standard error of b[x] is exactly the same.

I read the Stata user guide and scanned the web to find some hints, but unsuccessfully. I don't understand why the standard error of the overdispersion parameter is so different, and don't know which command I should use.

Have you already encountered such a problem with the jackknife command?

Many thanks in advance for your help!

Best,
Marc


      
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