Using the data in the table below, estimate a demand function for cod.

Price, dollars per pound

Quantity, thousand pounds per day

1.90

1.5

1.35

2.2

1.25

4.4

1.20

5.9

0.95

6.5

0.85

7.0

0.73

8.8

0.25

10.1

a) What are the estimated coefficients and what would you say about their statistical significance (at 95% and 99% confidence intervals)?

b) Comment on the regression output of R2 and adjusted R2. Why are they different?

c) Is the regression F-statistics significant and what does it measure?

d) Obtain the price elasticity of demand at each price level in the Table.

e) Suppose, you decided to estimate a nonlinear version of the regression using log() of the variables (quantity and price). Estimate a regression with these new variables.

f) What are the estimated coefficients and what would you say about their statistical significance (at 95% and 99% confidence intervals)?

g) Comment on the regression output of R2 and adjusted R2. Are they higher or lower than the linear version?

h) Obtain the price elasticity of demand from this nonlinear regression.

i) Suppose you are asked to make a prediction for the price level of 0.95. What would be the quantity demanded predictions from linear and nonlinear models?