In agricultural economics, a “supply response function” describes how supply of a commodity responds to changes in the price of that commodity.
(a) Estimate a supply response function for canola in Manitoba for the years 1966 to 2021. Carefully explain your model, fully reference your dataset (you will have to find the data), and fully interpret your results.
(b) Test the hypothesis that canola response does not elicit a supply response. Be sure to complete all parts of the hypothesis test. Think carefully about your rejection region(s).
(c) Construct a 95% confidence interval for your slope parameter. What does this tell you?
(d) Find the expected price for canola for the next crop year (explain why you think the price of canola will take on the value you pick), then predict how much canola will be seeded in Manitoba next year based upon this price. Based upon recent trends in Manitoba, justify why you do or do not think this is a reasonable prediction.
(e) Using the Jarque-Bera test, determine whether the data series used in this question are normally distributed. Show all your work.
(f) Re-estimate your model, using only the last 30 years of data. How do your results change? Why do you think this is, and what does it tell you about the robustness of your model?
(g) Re-estimate your model, using only the last 30 years of data, using a log-log functional form. Fully interpret your results, especially the interpretation of your new slope parameter.
(h) What other variables do you think could/should be added to this model to make it better? Write out your expanded model in econometric notation. Carefully describe why any variables you add would improve the model. Ensure any variables you add keep the model consistent with Koutsoyiannis’ desirable properties of any econometric model. (10 marks)
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