1. Canola is a very important field crop in Canada. Estimate the following model:
Where: ACt is the acreage (area planted) of canola in Canada in year t; PCt-1 is the price of canola in the previous year; PWt-1 is the price of wheat in the previous year; ACt-1 is the acreage of canola in the previous year; and et is the error term. Use data for 1980 – 2020. Everything should be converted to acres and dollars per bushel as needed; do not report things in hectares or tonnes.
(a) Estimate the model above and fully report/interpret your results. (30 marks)
(b) Test for autocorrelation using the Lagrange Multiplier test (you cannot use the bounds test because this model has a lagged dependent variable). (10 marks)
(c) If there is autocorrelation, correct for it using Generalized Least Squares. If there is no A/C, you do not have to correct for it. (10 marks)
(d) It is customary to truncate (i.e “cut off”) the lag lengths (i.e. whether you use (t-1), (t-2), or go even further back) for acreage at the point where they are no longer statistically significant. Re-estimate the above, but find the appropriate lag length for acreage. It might turn out to be two years, but it might not (that was just my guess). Find the correct lag length. (10 marks)
(e) Some might hypothesize that structural change occurred in the canola market around 2006. Check whether this occurred. (10 marks)
For the canola data, here is the link: https://www.gov.mb.ca/agriculture/markets-and-statistics/statistics-tables/pubs/canola-prodn.pdf
For the wheat data, here is the link: https://www.gov.mb.ca/agriculture/markets-and-statistics/statistics-tables/pubs/wheat-prodn.pdf
We just need to use ONLY data from 1980-2020, you can copy and put into excel sheet and conduct analysis.