Thank you very much JMMB
José M. M. Belbute, Ph.D. *Department of Economics | Centre for Advanced Studies in Management and Economics (CEFAGE)* On Sat, Dec 5, 2015 at 3:41 PM, Allin Cottrell <cottrell(a)wfu.edu> wrote: > On Sat, 5 Dec 2015, José Belbute wrote: > > Yes, >> >> I’m referring to time dummy variables to control for a (previously) known >> (or unknown) structural break at a specific point um time, whatever the >> frequency of our dataset – daily, weekly, monthly,…. >> >> In particular, consider the fooling equation to be estimated >> >> y(t)=a0+b0t+a1DM+b1DT+x(t) >> >> where t is time, ai and bi (with i=0,1) are parameters, y and x are >> observed variables – for example, inflation and unemployment, – and DM and >> DT are the needed dummies. The dummies take the following values: DM =1 if >> t>TB and DM=0, otherwise, and DT = (t-TB) if t>TB and DM=0 otherwise. Note >> that TB is the time of a possible structural change. >> >> Clearly, it is quite simple to generate and include these time dummies in >> our dataset using excel format files. >> >> My point is how to generate these dummies using gretl. >> > > scalar TB = <whatever you want> > series DM = t > TB > series DT = t > TB ? t - TB : 0 > > where "t" is a built-in time variable that starts at 1. You should take a > look at the Hansl Primer (it's under the Help menu). > > Allin Cottrell > > > >
Thank you very much
JMMB
José M. M. Belbute, Ph.D.
Department of Economics | Centre for Advanced Studies in Management and Economics (CEFAGE)
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On Sat, Dec 5, 2015 at 3:41 PM, Allin Cottrell <cottr...@wfu.edu> wrote:
On Sat, 5 Dec 2015, José Belbute wrote:
Yes,
Iâm referring to time dummy variables to control for a (previously) known
(or unknown) structural break at a specific point um time, whatever the
frequency of our dataset â daily, weekly, monthly,â¦.
In particular, consider the fooling equation to be estimated
y(t)=a0+b0t+a1DM+b1DT+x(t)
where t is time, ai and bi (with i=0,1) are parameters, y and x are
observed variables â for example, inflation and unemployment, â and DM and
DT are the needed dummies. The dummies take the following values: DM =1 if
t>TB and DM=0, otherwise, and DT = (t-TB) if t>TB and DM=0 otherwise. Note
that TB is the time of a possible structural change.
Clearly, it is quite simple to generate and include these time dummies in
our dataset using excel format files.
My point is how to generate these dummies using gretl.
scalar TB = <whatever you want>
series DM = t > TB
series DT = t > TB ? t - TB : 0
where "t" is a built-in time variable that starts at 1. You should take a look at the Hansl Primer (it's under the Help menu).
Allin Cottrell
