1.10 Consider again the following estimated model: Y = Bo+B+Bzxzi+B3x3i+ẞ4x4i + U₁ Given below is part of the regression output with and without robust standard errors: Coefficient SE P-value Robust SE P-value Constant 5.00 1.20 0.001 1.30 0.002 2.50 0.80 0.003 1.10 0.023 X21 -1.80 0.90 0.045 1.20 0.080 X31 6.65 1.65 0.001 1.76 0.001 X4i 3.50 0.50 0.001 0.66 0.001 Suppose you are writing your final report to a manager who cares only about results that pass all the relevant diagnostic tests. Which results should you focus on? Interpret the coefficients ẞ₁ and ẞ2 at the 5% level of significance. [5]

5. The following estimated equation was obtained by OLS regression using quarterly data for 1978 to 1996 inclusive. Yt = 2.20+ 0.104Xt₁ - 3.48 Xt₂ + 0.34Xt3 (3.4) (0.005) (2.2) (0.15) Standard errors are in parentheses, the explained sum of squares was 109.6, and the residual sum of squares 18.48. a. Test at the 5% level for the statistical significance of the parameter estimates. b. Calculate the coefficient of determination.

You estimated a regression with the following output.         Source |       SS           df       MS      Number of obs   =       268 -------------+----------------------------------   F(1, 266)       =     23.48        Model |  668419.175         1  668419.175   Prob > F        =    0.0000     Residual |  7572666.51       266  28468.6711   R-squared       =    0.0811 -------------+----------------------------------   Adj R-squared   =    0.0777        Total |  8241085.68       267  30865.4895   Root MSE        =    168.73   ------------------------------------------------------------------------------            Y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval] -------------+----------------------------------------------------------------            X |   1.014128   .2092916     4.85   0.000     .6020489    1.426207        _cons |   9.173163   21.13463     0.43   0.665    -32.43929    50.78561…

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