Suppose that there is a high degree of correlation (but not perfect) between education, age, and marital status. True or False: We should be concerned about this high degree of correlation because it affects our ability to reliably estimate the impact of the training program on 1998 earnings, T.

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earn98 = 4.84 + 2.429train+0.372earn96+0.365educ – 1.84 age + 2.446 married
(1.06)
(0.44)
(0.011)
(0.063)
(0.016)
(0.49)
where
earn98 = 1998 earnings, in thousands of dollars
train =1 if the individual participated in the training program, and =0 otherwise
earn96 = 1996 earnings, in thousands of dollars
educ = years of education
age = age, in years
married =1 if the individual is married, and =0 otherwise
Suppose that there is a high degree of correlation (but not perfect) between education, age, and marital status.
True or False: We should be concerned about this high degree of correlation because it affects our ability to reliably estimate the impact of the training
program on 1998 earnings, T.
True
False
Transcribed Image Text:earn98 = 4.84 + 2.429train+0.372earn96+0.365educ – 1.84 age + 2.446 married (1.06) (0.44) (0.011) (0.063) (0.016) (0.49) where earn98 = 1998 earnings, in thousands of dollars train =1 if the individual participated in the training program, and =0 otherwise earn96 = 1996 earnings, in thousands of dollars educ = years of education age = age, in years married =1 if the individual is married, and =0 otherwise Suppose that there is a high degree of correlation (but not perfect) between education, age, and marital status. True or False: We should be concerned about this high degree of correlation because it affects our ability to reliably estimate the impact of the training program on 1998 earnings, T. True False
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