A while ago, Sven, I started replicating Thomas&Christian's recession probability forecasting exercise using gretl's probit environment and lags of the dependent. It works quite well actually.
If I remember correctly the Kauppi/Saikonnen framework uses the lagged estimated probabilites instead of the observable, right?

Artur

Am 26. Mai 2016 23:11:50 MESZ, schrieb "Riccardo (Jack) Lucchetti" <r.lucchetti@univpm.it>:
On Thu, 26 May 2016, Sven Schreiber wrote:

Am 26.05.2016 um 17:57 schrieb Riccardo (Jack) Lucchetti:
On Thu, 26 May 2016, Sven Schreiber wrote:


From the abstract: "... it shows in a time series setting the
validity of the dynamic probit likelihood procedure when lags of the
dependent binary variable are used as regressors ..."

Does gretl rely on this particular paper's findings?

Well, in a way.

Section 3 states quite clearly that maximising the standard
log-likelihood gives you perfctly standard inference.

Right. Follow-up: What about h-step forecasting? Does gretl do it in this
case (I know, I should just try for myself...) and if so, does it do the
right thing? AFAI remember the forecasting was one of the main topics of
Kauppi&Saikkonen.

I don't know, I haven't read that one. You mean ReStat 2008, right? I'll
read it asap.



Riccardo (Jack) Lucchetti
Dipartimento di Scienze Economiche e Sociali (DiSES)

Università Politecnica delle Marche
(formerly known as Università di Ancona)

r.lucchetti@univpm.it
http://www2.econ.univpm.it/servizi/hpp/lucchetti



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