Am 19.12.2024 um 20:13 schrieb Sven Schreiber:
Hi all,
I just observed the following unwanted behavior; this is with gretl
2024d, but probably not brand new:
- I have a short yearly dataset spanning 2013-2023. (Confidential,
cannot share it here.)
- There are 14 time series in it, and somewhere in the middle is a
binary dummy, although its "discrete" flag in the attributes is _not_
set. Don't know whether that matters.
- Via the menu I add another obs to the dataset, for the year 2024.
- All variables have missings for the new obs, as expected, _except_
the dummy: it has a (spurious) value 1 for the new obs. This is wrong.
Hi and happy new year to all devels,
I tried to replicate this problem with a public dataset, but that wasn't
so easy. So I looked again at the dummy in my private dataset, and the
values are:
2013 0
2014 0
2015 1
2016 0
2017 0
2018 1
2019 0
2020 0
2021 1
2022 0
2023 0
So could it be that gretl is applying a heuristic that every third obs
of this dummy should be 1? Effectively treating it as some kind of
seasonality. But again, this is wrong for what this dummy represents. So
I'd suggest that seasonal extrapolation shouldn't be tried if the
dataset's $pd is ==1.
thanks
sven