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RE: st: RE: Standard error

From   "Maarten Buis" <>
To   <>
Subject   RE: st: RE: Standard error
Date   Fri, 20 Apr 2007 16:22:22 +0200

--- Joanne Marshall wrote:
> but if i was asked to compare the Standard error of the variable wage 
> (one of the independent variable) for two regression (one OLS and one 
> under heckit), and found out the SE for wage is bigger in heckit, than 
> OLS, what does that imply?

Typically you would compare standard errors with the estimated 
regression parameter. The z-statistic is the regression parameter 
divided by the standard error. To see whether that is large or small you 
look at the p-value. Comparing standard errors (or p-values) across 
models is not a good idea (Gelman and Stern 2006). So if you were asked
to do that than your answer should be: "it is wrong to do that" 
(probably with some explanation of why that's the case). However, given 
the initial confusion about terms, I would first double check if you 
understood the request correctly.

> also for rho, i had an estimate for 0.38, but no chi result. what does the
> 0.38 reflect?

Are you using the -heckman- command to estimate a heckit model? If so, and 
you are getting no chi2 value your model, than that probably means that you 
need to correct you model. If not, you probably should switch to -heckman-. 
The rho is the correlation between error terms. See for instance: 
(Breen 1996) or (Long 1997).

Hope this helps,

Andrew Gelman and Hal Stern (2006) The difference between ``significant'' 
and ``not significant'' is not itself statistically significant. American 
Statistician 60(4) pp.  328-331. 
( )

Richard Breen (1996) Regression models: Censored, sample selected, or 
truncated data. Thousand Oaks: Sage. 

J. Scott Long (1997) Regression models for categorical and limited dependent 
variables. Thousand Oaks: Sage

Maarten L. Buis
Department of Social Research Methodology 
Vrije Universiteit Amsterdam 
Boelelaan 1081 
1081 HV Amsterdam 
The Netherlands

visiting address:
Buitenveldertselaan 3 (Metropolitan), room Z434 

+31 20 5986715

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