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2,03… Show more TABLE 22 Year PIX HDI Gas 1 53.8 1,638.3 9

Paper help Economics 2,03… Show more TABLE 22 Year PIX HDI Gas 1 53.8 1,638.3 9

Economics

2,03… Show more TABLE 22 Year PIX HDI Gas 1 53.8 1,638.3 9

2,03… Show more 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? • Show less

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