10 pts Based on 50 years of annual data you suspect there is evidence of serial correlation between the returns for a large public commodity company, LNP, in the current period and price changes in raw commodity inputs from the previous period. Using LNP as the dependent variable you concluded there is a problem with serial correlation and decide to conduct a Generalized Least Squares (GLS) correction leading to the following results: SST: 10.2282. SSR 10.2277 Coefficient Standard Error Intercept: 0.020 0.00033 Slope: 1.502 0.00235 Lagged Slope p: -0.995 0.01376 You are also given the following data: Commodity LPN Returns Price Changes Current Year: 23.70% 4.47% Last Year: 7.66% 13.77% 2 Years ago 41.09% 16.06% Based on the above model and results, what is your estimate of what LPN's returns will be next year if you forecast that the price increase in Commodity Inputs will be 1.50%. 10 pts Based on 50 years of annual data you suspect there is evidence of serial correlation between the returns for a large public commodity company, LNP, in the current period and price changes in raw commodity inputs from the previous period. Using LNP as the dependent variable you concluded there is a problem with serial correlation and decide to conduct a Generalized Least Squares (GLS) correction leading to the following results: SST: 10.2282. SSR 10.2277 Coefficient Standard Error Intercept: 0.020 0.00033 Slope: 1.502 0.00235 Lagged Slope p: -0.995 0.01376 You are also given the following data: Commodity LPN Returns Price Changes Current Year: 23.70% 4.47% Last Year: 7.66% 13.77% 2 Years ago 41.09% 16.06% Based on the above model and results, what is your estimate of what LPN's returns will be next year if you forecast that the price increase in Commodity Inputs will be 1.50%