The file OIL.GDP.xls contains annual time series data for country Z in Africa. The variables in this data set are: Inflation (INFL) measured as a percentage, oil price (OILP) measured in dollars per barrel, percapita GDP (RGDP), measured in US dollars, and the real effective exchange rate (REER), measured as an index (increases by a unit). As an oil analyst, you suggest that the only way to study the impact of crude oil prices on macroeconomic activity in country Z is to regress the log of RGDP on a constant, log of OILP, log of INFL and log of REER.

(a) Estimate the above relationship using ordinary least squares and write the fitted regression equation.

(b) Interpret the estimated coefficients excluding the constant.

(c) Interpret the R-squared value of the model and briefly comment on the significance of each independent variable.

(d) Conduct and interpret the Durbin Watson test for autocorrelation. Alpha is given as 0.05.

(e) Test for the presence of heteroskedasticity in the model estimated in part (a). State the null and alternative hypotheses.

(f) What are the consequences of heteroskedasticity if it exists in a regression model?

(g) Conduct the general F-test on the model coefficients in part (c) using α = 5%

h) Using economic theory and the estimated model results in part (a), state whether country Z is a net importer or exporter of crude oil. Give evidence to support your answer.

I) If above estimation in part (a) has parameters instability then please rectify this problem and estimate the correct regression and note down the values involved for each of the classical assumptions and other tests.

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A 1 YEAR 2 1980 3 1981 4 1982 5 1983 6 1984 7 1985 8 1986 9 1987 10 1988 11 1989 12 1990 13 1991 14 1992 15 1993 16 1994 17 1995 18 1996 19 1997 20 1998 21 1999 22 2000 23 2001 24 2002 25 2003 26 2004 27 2005 28 2006 29 2007 30 2008 24 B INFL C OILP 9.97 35.7067 34.0383 D E REER RGDP 336.064 3096.21 20.555 373.052 3741.41 7.698 31.5442 382.648 3702.01 23.212 29.4692 453.121 3515.04 39.582 28.5458 626.377 3443.98 5.525 27.3708 561.631 3730.62 5.361 14.1717 306.766 3404.03 10.199 18.1983 97.7012 3038.04 34.499 14.7692 98.2511 3267.19 50.467 17.9058 87.4433 3478.48 7.364 22.985 80.7374 3922.54 12.695 19.3675 69.2978 3898.31 44.808 19.0358 57.4814 3915.22 57.165 16.7867 62.9682 3997.06 57.032 15.9483 116.647 4033.42 72.852 17.2042 98.8929 4021.02 29.262 20.3733 121.686 4221.82 8.536 19.2675 138.675 4340.12 9.986 13.0742 157.77 4457.99 6.617 17.9808 79.4988 4479.13 6.938 28.2342 80.4705 4717.33 18.032 24.3308 89.4329 5102.47 13.681 24.95 89.3128 6183.03 14.023 28.8917 84.4739 6822.07 15.02 37.76 86.7686 7544.19 17.818 53.3542 100 7951.01 8.34 64.2725 107.253 8444.85 5.465 71.1275 105.179 8989.53 11.235 97.035 216.476 9564.64 A 1 YEAR 2 1980 3 1981 4 1982 5 1983 6 1984 7 1985 8 1986 9 1987 10 1988 11 1989 12 1990 13 1991 14 1992 15 1993 16 1994 17 1995 18 1996 19 1997 20 1998 21 1999 22 2000 23 2001 24 2002 25 2003 26 2004 27 2005 28 2006 29 2007 30 2008 24 B INFL C OILP 9.97 35.7067 34.0383 D E REER RGDP 336.064 3096.21 20.555 373.052 3741.41 7.698 31.5442 382.648 3702.01 23.212 29.4692 453.121 3515.04 39.582 28.5458 626.377 3443.98 5.525 27.3708 561.631 3730.62 5.361 14.1717 306.766 3404.03 10.199 18.1983 97.7012 3038.04 34.499 14.7692 98.2511 3267.19 50.467 17.9058 87.4433 3478.48 7.364 22.985 80.7374 3922.54 12.695 19.3675 69.2978 3898.31 44.808 19.0358 57.4814 3915.22 57.165 16.7867 62.9682 3997.06 57.032 15.9483 116.647 4033.42 72.852 17.2042 98.8929 4021.02 29.262 20.3733 121.686 4221.82 8.536 19.2675 138.675 4340.12 9.986 13.0742 157.77 4457.99 6.617 17.9808 79.4988 4479.13 6.938 28.2342 80.4705 4717.33 18.032 24.3308 89.4329 5102.47 13.681 24.95 89.3128 6183.03 14.023 28.8917 84.4739 6822.07 15.02 37.76 86.7686 7544.19 17.818 53.3542 100 7951.01 8.34 64.2725 107.253 8444.85 5.465 71.1275 105.179 8989.53 11.235 97.035 216.476 9564.64

Answer rating: 100% (QA)

a To estimate the relationship using ordinary least squares we regress the log of RGDP on a constant log of OILP log of INFL and log of REER Let Y be the log of RGDP 1X1 be the log of OILP 2X2 be the ... View the full answer