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Hi,
I am looking for appropriate analysis steps or procedures that will enable
me to match production trends based on cumulative production. Below dataset
has historical production reported from multiple regions.
data have;
input region $ year prod;
datalines;
A 2000 100
A 2001 200
A 2002 250
A 2003 275
A 2004 450
A 2005 500
A 2006 300
A 2007 150
A 2008 75
A 2009 25
B 2004 125
B 2005 200
B 2006 250
B 2007 300
B 2008 425
C 2000 150
C 2001 450
C 2002 500
C 2003 550
C 2004 900
C 2005 1000
C 2006 750
C 2007 600
D 2006 125
D 2007 500
D 2008 550
D 2009 600
;
run;
If the production history of a region spans <= 5 years (as in B and D) then
the production trend is matched with trends from other regions which have
longer production history (based on cumulative production). From the above
dataset, B (cumulative production = 1300) is matched with A (1275 over 5
years) and D (1775) with C (1650 over 4 years). Assuming the same future
trend as A, production from B is predicted for the remaining number of
years. That is, production from region B is predicted for 5 more years.
Likewise, future production from D is predicted based on production from C.
In this case, production from D is predicted for 4 more years.
The example above is only a subset of the actual data. Therefore, trend
matching in my actual dataset may need to be done by comparing data from a
larger number of regions. I am looking for an efficient way to accomplish
this. Any suggestions?
Thank you in advance.
Sid
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