- This Exercise Is Based On Empirical Exercise 5 1 That Examines The Relationship Between A Worker S Age And Earnings Ins 1 (111.37 KiB) Viewed 9 times
This exercise is based on Empirical Exercise 5.1 that examines the relationship between a worker's age and earnings. Instead of the full dataset, you will analyze a subset of 500 individuals that you can download at this link. Open the file in Excel and estimate the following linear regression model: AHE = beta0 + beta1 *AGE + error where AHE and AGE refer to the (average hourly) earnings and age of an individual (and there are 500 individuals in your sample). The unit of AHE is dollars per hour and the unit of AGE is years. Answer the following questions: Calculate the test statistic for the null hypothesis H0: beta1 = 0 against the alternative H1: beta1 not= 0: t = Is AGE statistically significant at 10%? (type YES or NO) and 1%? What is the p-value associated with the coefficient's t-statistic? (if the pvalue is smaller than 0.01 type 0.00) Construct a 90% confidence interval for the slope coefficient of AGE: ( It can be argued that AGE should have a positive effect on earnings (more experience?). Test this hypothesis by performing a one-sided test that H0: beta1 <= 0 against H1: beta1 > 0. The t-statistic in this case is so that the conclusion for the and the 1% critical value is null hypothesis HO is (type REJECT or DO NOT REJECT) SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Intercept age 0.15696135 0.024636866 0.022678305 9.701436489 df 500 SS MS F 1 1183.91507 1183.91507 12.57906783 498 46870.69923 94.11786994 499 48054.6143 at 5%? Significance F 0.000426953 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 3.452726828 4.389771415 0.786539093 0.43192584 -5.172028196 12.07748185 -5.172028196 12.07748185 0.524793897 0.14796689 3.546698159 0.000426953 0.23407758 0.815510214 0.23407758 0.815510214