This exercise is based on the following data set.

a. Compute the ordinary least squares regression of Y on a constant, X1, and X2. Be sure to compute the conventional estimator of the asymptotic covariance matrix of the OLS estimator as well.

b. Compute the White estimator of the appropriate asymptotic covariance matrix for the OLS estimates.

c. Test for the presence of heteroscedasticity using White??s general test. Do your results suggest the nature of the heteroscedasticity?

d. Use the Breusch??Pagan Lagrange multiplier test to test for heteroscedasticity.

e. Sort the data keying on X1 and use the Goldfeld??Quandt test to test for heteroscedasticity. Repeat the procedure, using X2. What do youfind?

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-1.42 2.75 -0.26 -4.87 -0.62 7.01 26.14 -1.26 -0.15 3.41 5.51 -15.22 -1.47 -0.35 -0.48 1.24 -1.65 -0.63 -1.78 -0.80 0.02 -0.18 -0.67 -0.74 0.61 1.77 1.87 2.01 2.10 5.94 1.48 0.77 0.34 0.35 1.25 0.22 -1.32 0.33 -1.62 0.70 -1.87 2.32 2.92 -3.45 1.26 0.16 -1.99 0.39 0.32 1.56 4.38 -1.94 -0.88 -2.02 50 Observations on Y: -5.08 1.00 2.21 0.90 7.39 1.93 1.52 1.78 -5.45 -1.48 0.69 1.49 -6.87 0.79 1.31 1.06 0.70 0.17 6.66 1.91 50 Observations on X₁: 0.67 0.23 0.79 -1.04 1.25 0.68 0.77 -0.12 -0.60 -0.17 1.02 0.66 0.79 0.33 50 Observations on X₂: 2.88 -0.19 -1.28 0.37 -2.07 1.20 2.16 1.51 0.30 2.09 1.50 -0.46 -1.53 1.42 -2.70 1.91 -2.23 0.16 1.61 1.97 2.04 2.62 -0.40 0.28 1.06 0.86 0.48 -2.72 0.26 -0.17 0.19 1.77 -1.11 2.11 -23.17 3.00 -5.16 -1.13 0.58 -0.66 2.04 1.90 1.66 -3.82 -2.52 6.31 -4.71 0.15 -0.41 -1.18 -0.51 -0.18 -0.70 -1.55 -1.34 -2.10 7.82 -1.15 -0.39 1.54 -1.89 -1.85