The following regression was fitted by least squares to 32 annual observations on time-series data:

where
yt = quantity of U.S. wheat exported
x1t = price of U.S. wheat on world market
x2t = quantity of U.S. wheat harvested
x3t = measure of income in countries importing U.S. wheat
x4t = price of barley on world market
The numbers below the coefficients are the coefficient standard errors.
a. Interpret the estimated coefficient on log x1t in the context of the assumed model.
b. Test at the 5% level the null hypothesis that, all else being equal, income in importing countries has no effect on U.S. wheat exports against the alternative that higher income leads to higher expected exports. (Ignore, for now, the Durbin-Watson d statistic.)
c. What null hypothesis can be tested by the d statistic? Carry out this test for the present problem, using a 1% significance level.
d. In view of your finding in part c, comment on your conclusion in part b. How might you proceed to test the null hypothesis of part b?

Transcribed Image Text:

log y, = 4.52-0.62 log xịt + 0.92 logy + 0.61 log x3t (028) (038) (0.21) + 0.16 log x4t + e, R2-0.683 d = 0.61 (0.12)