data a;
input year x y;
lnx=log(x);
lny=log(y);
cards;
1978 133.6 116.1
1979 160.7 134.5
1980 191.3 162.2
1981 223.4 190.8
1982 270.1 220.2
1983 309.8 248.3
1984 355.3 273.8
1985 397.6 317.4
1986 423.8 357
1987 462.6 398.3
1988 544.9 476.7
1989 601.5 535.4
1990 686.3 584.6
1991 708.6 619.8
1992 784 659.8
1993 921.6 769.7
1994 1221 1016.8
1995 1577.7 1310.4
1996 1926.1 1572.1
1997 2090.1 1617.2
1998 2162 1590.3
1999 2210.3 1577.4
2000 2253.4 1670.1
2001 2366.4 1741
2002 2476 1834
;
proc gplot data=a;
plot lnx*year=1 lny*year=2/overlay;
symbol1 c=black i=join v=circle;
symbol2 c=black i=join v=star;
proc arima data=a;
identify var=lnx stationarity=(adf);
identify var=lny stationarity=(adf);
identify var=lnx(1) stationarity=(adf);
identify var=lny(1) stationarity=(adf);
identify var=lnx(1) stationarity=(pp);
identify var=lny(1) stationarity=(pp);
proc reg data=a;
model lny=lnx /noint;
output out=out residual=residual;
proc arima data=out;
identify var=residual stationarity=(adf);
proc arima data=a;
identify var=lny crosscorr=(lnx);
estimate p=1 input=lnx noint;
forecast lead=10 id=year out=result;
data result;
set result;
y=exp(lny);
estimate=exp(forecast);
proc gplot data=result;
plot lny*year=1 forecast*year=2 /overlay;
plot y*year=1 estimate*year=2 /overlay;
symbol1 c=black i=none v=star;
symbol2 c=red i=join v=none;
data b;
set a;
ecm=lny-0.96832*lnx;
lag_ecm=lag(ecm);
dif_lnx=dif(lnx);
dif_lny=dif(lny);
proc reg data=b;
model dif_lny=dif_lnx lag_ecm /noint;
run;





319  proc reg data=a;
320  model lny=lnx /noint;
321  output out=out residual=residual;
ERROR: 
NOTE: The data set WORK.OUT has 0 observations and 0 variables.
WARNING: Data set WORK.OUT was not replaced because new file is incomplete.
求解释