On Fri, 4 Sep 2020, Fred Morkel wrote:
One example: In our model, we estimate energy consumption by sectors with real
production by sectors and the relative prices by sectors which is calculated as
energy prices by sectors divided by output prices by sectors.
For this example, we then have 20 regressions due to 20 sectors and thus need
to introduce 20 temporary variables which depict the aforementioned relative
prices by sectors.
As we have many more estimations like this, partly for many more than 20
sectors, you might get the picture. Most of the time, the temporary variables
would not be used further.
Does this explain the problem better?
Yes, thanks, this is much clearer. But in a case such as yours, I would
argue that a judicious use of loops would be advisable anyway. If
temnporary variables are a problem, deleting them after use within the
loop itself is rather simple. Better still, you could use a function and
the temporary variables would automagically disappear after use. For
example,
<hansl>
function void do_weird_regression(series y, series x)
series tmp1 = log(x)
series tmp2 = cos(x)
series tmp3 = x/exp(x)
ols y const tmp1 tmp2 tmp3
end function
nulldata 100
# generate example dataset
loop foreach i FOO BAR BAZ
series y_$i = normal()
series x_$i = uniform()
endloop
# example
do_weird_regression(y_FOO, x_FOO)
# better
loop foreach i FOO BAR BAZ
do_weird_regression(y_$i, x_$i)
endloop
</hansl>
-------------------------------------------------------
Riccardo (Jack) Lucchetti
Dipartimento di Scienze Economiche e Sociali (DiSES)
Università Politecnica delle Marche
(formerly known as Università di Ancona)
r.lucche...@univpm.it
http://www2.econ.univpm.it/servizi/hpp/lucchetti
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