The estimation results of two different models regarding consumption expenditures in the 2000- 2019 period are given below: Model 1: Y = B1 + B2X2t + B3X3t + B4X4t + B5X5t + B6X6 + ut Y = 1 + 12x2t + 13X3t+14X4+ + vt Model 2: Here, y denotes the dependent variable and Xi the independent variables. The regression findings based on 19 observations and obtained by SEK are as follows: P1 = 3,919 - 9,408X2+ + 0,04048X31 - 0,3313X4 - 0,4725X5t + 3,991X6t (0,925) (-1,729) (0,324) (-1,942) (-0,315) (1,949) R2 = 0,8658 Y = 2,721 - 0,6766X2 +0,001136X3+ + 0,001222X41 t (1,361) (-0,253) (8,166) (4,193) R2 = 0,8348 a-) Can you talk about a possible multicollinearity problem in the first model by examining the regression results of the first and second models together? Explain why you suspect multicollinearity in at most three sentences. b-) X11 = Q1 + azXz1+&i The r2 value of the auxiliary binding was found to be 0.999998. Explain how you can benefit from this result in a maximum of three sentences. C-) Is the relationship between the variables X1 and X2 a full collinearity relationship? Explain the reason in at most two sentences. The estimation results of two different models regarding consumption expenditures in the 2000- 2019 period are given below: Model 1: Y = B1 + B2X2t + B3X3t + B4X4t + B5X5t + B6X6 + ut Y = 1 + 12x2t + 13X3t+14X4+ + vt Model 2: Here, y denotes the dependent variable and Xi the independent variables. The regression findings based on 19 observations and obtained by SEK are as follows: P1 = 3,919 - 9,408X2+ + 0,04048X31 - 0,3313X4 - 0,4725X5t + 3,991X6t (0,925) (-1,729) (0,324) (-1,942) (-0,315) (1,949) R2 = 0,8658 Y = 2,721 - 0,6766X2 +0,001136X3+ + 0,001222X41 t (1,361) (-0,253) (8,166) (4,193) R2 = 0,8348 a-) Can you talk about a possible multicollinearity problem in the first model by examining the regression results of the first and second models together? Explain why you suspect multicollinearity in at most three sentences. b-) X11 = Q1 + azXz1+&i The r2 value of the auxiliary binding was found to be 0.999998. Explain how you can benefit from this result in a maximum of three sentences. C-) Is the relationship between the variables X1 and X2 a full collinearity relationship? Explain the reason in at most two sentences