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*** Introduction to ARIMA modeling in RATS.
***
*** See Examples 16.1, 17.3, 18.1 in Pindyck and Rubinfeld (4th Edition, 1998)
***  (P&R use data through March, 1996, ours ends in February, 1996)
***
*** This version uses BJIDEN and BJFORE procedures.
***
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*** Set the CALENDAR and ALLOCATE range. CAL to start in January, 1960:
*** and read in the Data:
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calendar 1960 1 12
allocate 1999:9
open data basics.wks
data(format=wks,organization=observation) / rate

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*** Look at stationarity:
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* Graph the original series:

graph(key=upleft)
# rate

source(noecho) bjident.src
@bjident(diff=2,trans=none) rate

* P&R settle on an ARIMA(8,1,4) with a constant:
* Estimate and compute 24-period ex poste forecats:

source(noecho) bjfore.src
@bjfore(ars=8,mas=4,diffs=1,constant,rend=1996:2) rate $
        1994:3 1996:2 rate_fore resids
smpl 1994:3 1996:2
graph(key=below,header='Interest Rate Forecast') 2
# rate
# rate_fore
smpl

* Eximine residual correlations:
@bjident(diff=0) resids

* 18-month ex ante forecast:
@bjfore(ars=8,mas=4,diffs=1,constant,rend=1996:2) rate $
        1995:10 1997:3 rate_fore18 resids

smpl 1995:10 1997:3
graph(key=below,header='Interest Rate Forecast') 2
# rate
# rate_fore18
smpl