1. A shoe manufacturer hired a consulting firm to provide forecasts for shoes in the United States. The consulting firm using linear regression analysis estimated the following equation for the period 1982 to 2020. The equation reports the estimated regression coefficients, their corresponding t-statistics (in parenthesis), the coefficient of determination, R and the Durbin-Watson statistic (D.W.). Qt = 19.575 +0.0289*C - 0.0923*Pt - 99.568*S - 4.06*D (9.3125) (-1.7682) (-9.896) R = 0.857 D.W. = 1.86 (23.50) Where Q = per capita personal consumption expenditures on shoes C = total per capita consumption expenditures P = price of shoes relative to all other goods and services S stock of shoes per capita D= 0 for years before 9/11/2001 (1982-2001) and D = 1 for years after 9/11/2001 (2002-2020) a. Interpret the R. b. Are each of the estimated coefficients statistically significant at the 5% level ( = 0.05), Year C P S 1996 1,646 2022 2,256 20 20 0.4 30 0.6 c. Given the information in the table above forecast the per-capita personal consumption expenditures for shoes for 1996. d. Given the information in the table above forecast the per-capita personal consumption expenditures for shoes for 2022. e. Which year do you believe will have the largest forecast error? Explain.