Dear all,
Please I will greatly appreciate if anyone can guide me on how to forecast this ARIMA model. I have a quarterly data of differenced producer price index (dppi) from 1960 to 2002 (giving 169 observations):
input float(t dppi)
1 .
2 .04000092
3 -.069999695
4 .02999878
5 .09000015
6 -.25
7 0
8 .04000092
9 .13999939
10 -.13999939
11 .12999916
12 -.03999901
13 -.09000015
14 -.04000092
15 .10000038
16 .02000046
17 .02999878
18 -.11999893
19 .07999992
20 .069999695
21 .1100006
22 .26000023
23 .18999863
24 .1499996
25 .4000015
26 .1099987
27 .29000092
28 -.1800003
29 -.01000023
30 -.03999901
31 .1099987
32 .05000114
33 .3699989
34 .17000008
35 .1100006
36 .13999939
37 .4200001
38 .3700008
39 .2099991
40 .2800007
41 .4200001
42 .13999939
43 .17000008
44 .04000092
45 .4399986
46 .3600006
47 .23999977
48 .02000046
49 .5699997
50 .3099995
51 .4700012
52 .34000015
53 1.5699997
54 1.6499977
55 1.4700012
56 .3199997
57 2.4799995
58 1.420002
59 2.9399986
60 1.540001
61 -.009998322
62 .4899979
63 .9900017
64 .5099983
65 .2400017
66 .7099991
67 .59000015
68 .4399986
69 1.1000023
70 1.2199974
71 .069999695
72 .6100006
73 1.2800026
74 1.619999
75 .8600006
76 1.2799988
77 2.0999985
78 2.130001
79 1.9400024
80 2.2599945
81 3.080002
82 1.3899994
83 2.340004
84 1.6899948
85 2.2300034
86 1.75
87 .5299988
88 -.08000183
89 .6700058
90 .08999634
91 .3600006
92 .08000183
93 .04999542
94 .2800064
95 .7699966
96 .4000015
97 .9199982
98 .55000305
99 -.20000458
100 -.2099991
end
format %tq t
[/CODE]
These are the commands that I executed and stored the results:
arima dppi, arima (3,1,3)
estimate store arima
Here is the output:
Kindly guide on how to forecast this model....or assist me with a dofile that I can modify, if you can.
Thank you.
Please I will greatly appreciate if anyone can guide me on how to forecast this ARIMA model. I have a quarterly data of differenced producer price index (dppi) from 1960 to 2002 (giving 169 observations):
input float(t dppi)
1 .
2 .04000092
3 -.069999695
4 .02999878
5 .09000015
6 -.25
7 0
8 .04000092
9 .13999939
10 -.13999939
11 .12999916
12 -.03999901
13 -.09000015
14 -.04000092
15 .10000038
16 .02000046
17 .02999878
18 -.11999893
19 .07999992
20 .069999695
21 .1100006
22 .26000023
23 .18999863
24 .1499996
25 .4000015
26 .1099987
27 .29000092
28 -.1800003
29 -.01000023
30 -.03999901
31 .1099987
32 .05000114
33 .3699989
34 .17000008
35 .1100006
36 .13999939
37 .4200001
38 .3700008
39 .2099991
40 .2800007
41 .4200001
42 .13999939
43 .17000008
44 .04000092
45 .4399986
46 .3600006
47 .23999977
48 .02000046
49 .5699997
50 .3099995
51 .4700012
52 .34000015
53 1.5699997
54 1.6499977
55 1.4700012
56 .3199997
57 2.4799995
58 1.420002
59 2.9399986
60 1.540001
61 -.009998322
62 .4899979
63 .9900017
64 .5099983
65 .2400017
66 .7099991
67 .59000015
68 .4399986
69 1.1000023
70 1.2199974
71 .069999695
72 .6100006
73 1.2800026
74 1.619999
75 .8600006
76 1.2799988
77 2.0999985
78 2.130001
79 1.9400024
80 2.2599945
81 3.080002
82 1.3899994
83 2.340004
84 1.6899948
85 2.2300034
86 1.75
87 .5299988
88 -.08000183
89 .6700058
90 .08999634
91 .3600006
92 .08000183
93 .04999542
94 .2800064
95 .7699966
96 .4000015
97 .9199982
98 .55000305
99 -.20000458
100 -.2099991
end
format %tq t
[/CODE]
These are the commands that I executed and stored the results:
arima dppi, arima (3,1,3)
estimate store arima
Here is the output:
| ARIMA regression | ||||
| Sample: 1960q4 - 2002q2 | Number of obs = | 167 | ||
| Wald chi2(6) = | 1049.13 | |||
| Log likelihood = -184.9708 | Prob > chi2 = | 0.0000 | ||
| | | OPG | |||
| D.dppi | Coef. | Std. Err. | z | P>|z| [95% Conf. | Interval] |
| dppi | | ||||
| _cons | -.0003337 | .0062978 | -0.05 | 0.958 -.0126771 | .0120098 |
| ARMA | | ||||
| ar | | ||||
| L1. | .1578491 | .0737047 | 2.14 | 0.032 .0133905 | .3023077 |
| L2. | -.6440201 | .0654338 | -9.84 | 0.000 -.772268 | -.5157721 |
| L3. | .6014706 | .0727478 | 8.27 | 0.000 .4588874 | .7440537 |
| | | ||||
| ma | | ||||
| L1. | -.6156038 | .0734836 | -8.38 | 0.000 -.759629 | -.4715785 |
| L2. | .5500884 | .0706142 | 7.79 | 0.000 .4116871 | .6884898 |
| L3. | -.8575131 | .0561864 | -15.26 | 0.000 -.9676364 | -.7473899 |
| /sigma | .7271178 | .0282967 | 25.70 | 0.000 .6716573 | .7825782 |
Thank you.
