BookmarkSubscribeRSS Feed
podarum
Quartz | Level 8

I need some guidance.  I need to forecast retail prices in certain geographical areas, so my dependent variable would be the prices itself, the independent variables could be factors such as 1) # of residents, 2) home prices, 3) unemployment rates 4) GDP .. etc. (the actual variables are just used as examples, not real variables)

My question is, if I want to forecast the prices, then MUSt I also forecast the independent variables if I want to use them in the model.. so eg. forecast the unemployment rate also for the next 12 months?  and question number 2 is using PROC ARIMA, how can I 1) determine which independent variables make sense to use in the model and 2) how and where in the proc arima statement do I insert these independent variables?

Thanks in advance.

1 REPLY 1
Snurre_SAS
SAS Employee

Hi,

With respect to a forecast model with inputs - unless you have a situation where the inputs lead the dependent (eg. unemployment goes up but prices doesn't change until 6 months later) you will need to forecast inputs as well.

With respect to the specific ARIMA questions I'd suggest having a look at the documentation: http://support.sas.com/documentation/cdl/en/etsug/63939/HTML/default/etsug_arima_sect001.htm and some of the examples - for instance this: http://support.sas.com/documentation/cdl/en/etsug/63939/HTML/default/etsug_arima_sect057.htm

Regards,

Snurre

SAS Innovate 2025: Register Now

Registration is now open for SAS Innovate 2025 , our biggest and most exciting global event of the year! Join us in Orlando, FL, May 6-9.
Sign up by Dec. 31 to get the 2024 rate of just $495.
Register now!

Multiple Linear Regression in SAS

Learn how to run multiple linear regression models with and without interactions, presented by SAS user Alex Chaplin.

Find more tutorials on the SAS Users YouTube channel.

Discussion stats
  • 1 reply
  • 1283 views
  • 0 likes
  • 2 in conversation