On Fri, 29 Jan 2021, Artur Bala wrote:
 Hi,
 Probably the topic of "How small is really small?" has been already
 discussed but I'm still a bit confused.
 Now, for the following estimation, Stata considers that std errors  are 0
 and provides no output. Instead, gretl reports quite small values resulting
 in very "optimistic" p-values.
 Obviously, the missing F statistic and a R2=1 should provoke doubt and
 question the validity of the model...though those *** seem confusing :).
 In such circumstances, is there a way to make gretl "judge" that std.errors
 are actually 0 and omit t tests? 
In my opinion, we need to take no such action. Let me explain my point.
The standard errors one see printed by the side of estimated coefficients 
are, per se, just descriptive statistics that give you an idea of how 
sensitive the objective function (the sum of squares) is to changes in 
that parameter. If that number is small, it means that small changes in 
that parameter make the model much worse in fitting the dependent 
variable. That's what the standard errors are.
That said, you _may_ give them an inferential interpretation and use them 
to construct hypothesis tests and confidence intervals, but then, the 
burden of correctly interpreting their meaning is on the user. The fact 
that many, in the economic profession, have come to the unfortunate habit 
of automatically thinking "no stars -> bad, two stars -> good, three stars 
-> wow" should not deter us, as authors of a statistical package, from 
reporting the statistic in the most precise way possible and refrain from 
patronising the user.
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   Riccardo (Jack) Lucchetti
   Dipartimento di Scienze Economiche e Sociali (DiSES)
   Università Politecnica delle Marche
   (formerly known as Università di Ancona)
   r.lucchetti(a)univpm.it
   
http://www2.econ.univpm.it/servizi/hpp/lucchetti
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