Consider the following estimated regression equation (standard errors in parentheses):

Where:

Y_t = the corn yield (bushels/acre) in year t

F_t = fertilizer intensity (pounds/acre) in year t

R_t = rainfall (inches) in year t

a. Carefully state the meaning of the coefficients 0.10 and 5.33 in this equation in terms of the impact of F and R on Y.

b. Does the constant term of -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 β_F 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 assumptions and therefore is not BLUE. Does this mean that the true β_R is definitely not equal to 5.33? Why or why not?