Consider the following estimated regression equation (standard errors in parentheses): where Y = 30 + 3pFt...

 

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Consider the following estimated regression equation (standard errors in parentheses): where Y = 30 + 3pFt + BR-120+0.10F, +5.33R₁, R² = 0.50 (1.00) Y, F, R₁ (0.05) the corn yield (bushels/acre) in year t fertilizer intensity (pounds/acre) in year t rainfall (inches) in year t (a) Carefully state the meaning of the coefficients 3p = 0.10 and BR = 5.33 in this equation in terms of the impact of F and R on Y. (b) Does the constant term of 30-120 really mean that negative amounts of corn are possible? If not, what is the meaning of that estimate? (c) Suppose you were told that the true value of 3 is known to be 0.20. Does this show that the estimate is biased? Why or why not? (d) Suppose you were told that the equation does not meet all the classical assump- tions and therefore is not BLUE. Does this mean that the true 5 is definitely not equal to 5.33? Why or why not? Consider the following estimated regression equation (standard errors in parentheses): where Y = 30 + 3pFt + BR-120+0.10F, +5.33R₁, R² = 0.50 (1.00) Y, F, R₁ (0.05) the corn yield (bushels/acre) in year t fertilizer intensity (pounds/acre) in year t rainfall (inches) in year t (a) Carefully state the meaning of the coefficients 3p = 0.10 and BR = 5.33 in this equation in terms of the impact of F and R on Y. (b) Does the constant term of 30-120 really mean that negative amounts of corn are possible? If not, what is the meaning of that estimate? (c) Suppose you were told that the true value of 3 is known to be 0.20. Does this show that the estimate is biased? Why or why not? (d) Suppose you were told that the equation does not meet all the classical assump- tions and therefore is not BLUE. Does this mean that the true 5 is definitely not equal to 5.33? Why or why not?