Compare and comment on the two following estimated models. Which one do you select for xt? Why? Dependent Variable: XT Method: Least Squares Date: 11/30/23 Time: 02:19 Sample: 1/02/2014 12/29/2023 Included observations: 2607 Convergence achieved after 4 iterations Dependent Variable: XT Method: Least Squares Date: 11/30/23 Time: 02:20 Sample: 1/02/2014 12/29/2023 Included observations: 2607 Convergence achieved after 2 iterations Variable Coefficient Std. Error t-Statistic Prob. c AR(1) 8.129559 0.995498 4.331842 0.001866 1.876698 533.3931 0.0607 0.0000 Variable Coefficient Std. Error t-Statistic Prob. AR(1) 0.997202 0.001465 680.7353 0.0000 R-squared: 0.990927 Adjusted R-squared: 0.990923 S.E. of regression: 0.995583 Sum squared resid: 2.834291 Log likelihood: 2.831421 F-statistic: 1.938672 Prob(F-statistic): 0.000000 Mean dependent var: 8.251970 S.D.dependent var: 10.45002 Akaike info criterion: 2.829791 Schwarz criterion: 2.834291 Hannan-Quinn criter.: 2.831421 Durbin-Watson stat: 0.000000 R-squared: 0.990919 Adjusted R-squared: 0.990919 S.E. of regression: 0.995806 Sum squared resid: 2.832106 Log likelihood: 2.830671 Durbin-Watson stat: 1.940361 Mean dependent var: 8.251970 S.D.dependent var: 10.45002 Akaike info criterion: 2.829856 Schwarz criterion: 2.832106 Hannan-Quinn criter.: 2.830671 Inverted AR Roots: 1.00 Inverted AR Roots: 1.00
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The only difference between the two models is the number of iterations it took to achieve convergence. The first model achieved convergence after 4 iterations, while the second model achieved convergence after 2 iterations. Show more…
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