Question

TABLE 22

Year	PIX	HDI	Gas
1	53.8	1,638.3	98185
2	56.9	1,825.3	124228
3	60.6	2,030.9	151907
4	65.2	2,294.7	176002
5	72.6	2,563.3	212007
6	82.4	2,789.5	249750
7	90.9	3,128.4	265067
8	96.5	3,255.0	247642
9	99.6	3,536.7	268901
10	103.9	3,933.2	332418
11	107.6	4,220.3	338088
12	109.6	4,462.8	368425
13	113.6	4,739.5	409765
14	118.3	5,103.8	447189
15	124.0	5,484.4	477665
16	130.7	5,803.1	498438
17	136.2	5,995.9	491020
18	140.3	6,337.7	536528
19	144.5	6,657.4	589394
20	148.2	7,072.2	668690
21	152.4	7,397.7	749374
22	156.9	7,816.9	803113
23	160.5	8,304.3	876470
24	163.0	8,747.0	917103
25	166.6	9,268.4	1029980
26	172.2	9,817.0	1224408
27	177.1	10,128.0	1145900
28	179.9	10,469.6	1164720
29	184.0	10,960.8	1260717
30	188.9	11,712.5	1472926
31	195.3	12,455.8	1677371

Refer to table 22 which gives data on Gas, HDI, and PIX for Iraq. Consider the following log-log model:

lnImports = B1 + B2 lnGDP + B3 lnCPI + u

***********************please use "SAS format" ************************* (where/if possible)

1) Estimate the parameters using the data given in the table 22.

2) Do you suspect that there is multicollinearity in the data? Why or why not?

3) Regress:

(a) ln GAS = A1 + A2 ln(HDI)

(b) ln GAS = B1 + B2 ln(PIX)

(c) ln HDI = C1+ C2 ln(PIX)

On the basis of these regressions, what could you say about the nature of multicollinearity in the data?

4) Suppose there is multicollinearity in the data but B2 and B3 are individually significant at the 5% level and the overall F test is also significant. In this case should we worry about the collinearity problem?