*
* Example of AR model starting page 245
*
open data inflation.dat
calendar(m) 1983:12
data(format=free,org=columns) 1983:12 2006:05 year month wage pcwage cpi infln
*
set y = 100*(log(cpi)-log(cpi{1}))
linreg y
# constant y{1 2 3}
@regcorrs(number=24)
*
* UFORECAST does Univariate Forecasts using the last regression. The first
* parameter is the target series for the forecast; the second and third give the
* range that you want to forecast. You can use the STDERRS option to get the
* series of estimated standard errors for the forecasts. As described in the text,
* those are calculated as if the coefficients are known.
*
uforecast(stderrs=fstderrs) yfore 2006:6 2006:8
*
* Use yfore and fstderrs to compute the lower and upper bounds for the confidence intervals.
*
set lower 2006:6 2006:8 = yfore-%invttest(.05,%ndf)*fstderrs
set upper 2006:6 2006:8 = yfore+%invttest(.05,%ndf)*fstderrs
*
* Show the results with the output restricted to just four digits
*
print(picture="*.####") 2006:6 2006:8 yfore fstderrs lower upper