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st: RE: seasonality


From   "Nick Cox" <n.j.cox@durham.ac.uk>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: seasonality
Date   Fri, 1 Apr 2005 16:57:48 +0100

Welcome back after your hiatus. 

To centre a variable you need to go 

su y, meanonly 
gen yc = y - r(mean) 

except that this is such a common need
that users have created commands to 
do that for you. For example, look at Ben Jann's 
-center- on SSC: 

. ssc desc center 

Your question about seasonality is much 
fuzzier. There are lots of different ways 
of testing for seasonality. In the 
environmental sciences, I would usually 
try fitting sine and cosine terms given 
2 * pi * (position in year / length of year). 
That is, also, I guess a congenial approach 
for most natural scientists. 

With economic or social data other methods appear
more common, and may or may not be more 
appropriate. People seem happier with looking 
at lags 4, 12, whatever depending on whether 
data are quarterly, monthly, whatever. That may 
be what SAS command proc x12 does. But 
the adjustments seem much more complicated
given complications like holidays that are
irrelevant outside the human sphere.

In any case, graphics are often useful 
for getting a handle on seasonality and 
often surprising neglected by people like 
economists.  

Without knowing more about your data
or your research problem this is rather too
large a question to answer well. In short, the 
question may be quick but the answer isn't. 

Nick 
n.j.cox@durham.ac.uk 

kelly johnson
 
> I am returning to stata after a hatus of a couple of years. I 
> had two quick questions:
> 
> Suppose I am using a stream of time seies data for a single 
> varible (Data, Variable1):
> 
> (1) suppose i wanted to generate a new varible that equale 
> variable1 - the 
> mean of varible1. how do i do this (without having to create 
> a whole column 
> with only the mean of variable1 in it)?
> 
> (2) is there an easy wasy to test for seasonality? in sas we 
> have the proc 
> x12 command? what's a quickand eqasy way to test for 
> seasonality in data?
 

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