A researcher has designed the relationship between the salaries of selected employees of an organization (shown as "EARN" in $/hour) and their years of education (shown as "YRSEDUC", in years) and their age (shown as "AGE" in years). The estimated GRETL outcome is shown as hereunder (numbers are made up): Model 1: OLS, using observations 1-322 Dependent variable: EARN Coefficient std. error t-ratio p-value Const 12.40443 1.862341 43.854 4.06e-06 *** YRSEDUC 5.32901 0.195032 -1.032 4.62e-033 *** AGE 1.29003 1.002893 7.281 7.59e-040 *** Mean dependent var 10.27310 S.D. dependent var 4.758696 Sum squared resid 588266.3 S.E. of regression 8.584281 R-squared 0.289671 Adjusted R-squared 0.289430
A researcher has designed the relationship between the salaries of selected employees of an organization (shown as "EARN" in $/hour) and their years of education (shown as "YRSEDUC", in years) and their age (shown as "AGE" in years). The estimated GRETL outcome is shown as hereunder (numbers are made up): Model 1: OLS, using observations 1-322 Dependent variable: EARN Coefficient std. error t-ratio p-value Const 12.40443 1.862341 43.854 4.06e-06 *** YRSEDUC 5.32901 0.195032 -1.032 4.62e-033 *** AGE 1.29003 1.002893 7.281 7.59e-040 *** Mean dependent var 10.27310 S.D. dependent var 4.758696 Sum squared resid 588266.3 S.E. of regression 8.584281 R-squared 0.289671 Adjusted R-squared 0.289430
Chapter1: Making Economics Decisions
Section: Chapter Questions
Problem 1QTC
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Using the findings, to answer the following questions:
A-Write down the estimated regression equation,
B-Interpret the estimated slope coefficient of the variable "AGE".
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