Econometrics-I-7

# Store b(r endproc ends procedure

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Unformatted text preview: .. Store b(r) Endproc Ends procedure exec;n=20;bootstrap=b\$ 20 bootstrap reps matr;list;bboot' \$ Display results &#152;&#152;™™ ™ 16/35 Part 7: Estimating the Variance of b--------+------------------------------------------------------------- Variable| Coefficient Standard Error t-ratio P[|T|>t] Mean of X--------+------------------------------------------------------------- Constant| -79.7535*** 8.67255 -9.196 .0000 Y| .03692*** .00132 28.022 .0000 9232.86 PG| -15.1224*** 1.88034 -8.042 .0000 2.31661--------+------------------------------------------------------------- Completed 20 bootstrap iterations.---------------------------------------------------------------------- Results of bootstrap estimation of model. Model has been reestimated 20 times. Means shown below are the means of the bootstrap estimates. Coefficients shown below are the original estimates based on the full sample. bootstrap samples have 36 observations.--------+------------------------------------------------------------- Variable| Coefficient Standard Error b/St.Er. P[|Z|>z] Mean of X--------+------------------------------------------------------------- B001| -79.7535*** 8.35512 -9.545 .0000 -79.5329 B002| .03692*** .00133 27.773 .0000 .03682 B003| -15.1224*** 2.03503 -7.431 .0000 -14.7654--------+------------------------------------------------------------- Results of Bootstrap Procedure &#152;&#152;™™ ™ 17/35 Part 7: Estimating the Variance of b Bootstrap Replications Full sample result Bootstrapped sample results &#152;&#152;&#152;™™ ™ 18/35 Part 7: Estimating the Variance of b OLS vs. Least Absolute Deviations---------------------------------------------------------------------- Least absolute deviations estimator............... Residuals Sum of squares = 1537.58603 Standard error of e = 6.82594 Fit R-squared = .98284--------+------------------------------------------------------------- Variable| Coefficient Standard Error b/St.Er. P[|Z|>z] Mean of X--------+------------------------------------------------------------- |Covariance matrix based on 50 replications. Constant| -84.0258*** 16.08614 -5.223 .0000 Y| .03784*** .00271 13.952 .0000 9232.86 PG| -17.0990*** 4.37160 -3.911 .0001 2.31661--------+------------------------------------------------------------- Ordinary least squares regression ............ Residuals Sum of squares = 1472.79834 Standard error of e = 6.68059 Standard errors are based on Fit R-squared = .98356 50 bootstrap replications--------+------------------------------------------------------------- Variable| Coefficient Standard Error t-ratio P[|T|>t] Mean of X--------+------------------------------------------------------------- Constant| -79.7535*** 8.67255 -9.196 .0000 Y| .03692*** .00132 28.022 .0000 9232.86 PG| -15.1224*** 1.88034 -8.042 .0000 2.31661--------+------------------------------------------------------------- &#152;&#152;&#152;™™ ™ 19/35 Part 7: Estimating the Variance of b Multicollinearity...
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Store b(r Endproc Ends procedure exec;n=20;bootstrap=b\$ 20...

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