Am 23.08.2023 um 14:05 schrieb Alison Loddick:
I’m wondering if you can help me. Firstly, I am not an >
econometrician but a statistician, so I know I have lots to learn. I
generally use Gretl with students to teach them how to do panel >
regression
and correlation. ... > The student has 17 years of data and
wants to compare two variables > (pay and productivity) over 17 regions
to understand how the regions > differ over time and whether the two
measures have a relationship. > I’m wondering if it is some sort of
multivariate time series model. > > > > Can anyone help me help the
student?
Your question is quite broad I think, but I will try to answer as
gretl-specific as I can. You said you're teaching panel regressions, and
that's what I think is the natural approach here. Why not just run a
fixed-effects regression between the two variables? For example, using
the grunfeld sample dataset in gretl to regress 'value' on 'invest' with
the standard fixed effects, gretl reports a LSDV-R2 of 0.96 and a
within-R2 of 0.37. This is just to calculate a panel-context correlation
between the two variables, not as a model per se.
Of course then you have the usual panel-related questions on whether you
really want fixed effects and so on, but that's a different (and not
directly gretl-related topic).
I don't see this as a time series model in the usual sense, because with
17 regions and 2 panel variables you have 34 time series, but apparently
only 17 periods (years) of data. But if you want to have dynamic effects
in your panel regression is of course yet another question. Finally,
wanting to understand "how regions differ over time" strikes me as an
ambitious question in general, because then you would need some
interaction effects or maybe even time-varying parameters. Or maybe you
just want to calculate some statistics over rolling windows, that's of
course feasible (in principle, not saying there's a built-in function
for that).
cheers
sven