WageEqQ_handout

WageEqQ_handout - B2) Consider the following wage equation...

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B2) Consider the following wage equation that has been estimated from a sample of 35-65 year old older male workers in a single large company: Dependent variable: ln wage (1) (2) (3) Constant 3.825 3.441 3.582 12.10 12.11 12.04 Age 0.154 0.155 0.148 3.18 2.11 1.98 Age 2 -0.014 -0.013 -0.014 1.55 2.04 2.03 NT - 0.0091 0.0064 4.11 3.90 NT 2 - 0.0094 0.0026 3.91 3.27 NT 3 - -0.0006 -0.0001 4.06 3.84 EDUC 0.183 - 0.122 5.08 6.61 No of obs 4823 4823 4823 R 2 0.104 0.221 0.240 where Age is Age in years divided by 10; NT is a variable indicating the total number of days of training courses workers have taken over their career and EDUC is a dummy variable indicating if the individual has higher education qualifications. Numbers in italics are absolute t-ratios. a) Taking the specification in column (1), at what age are wages predicted to be highest? Is there statistically significant evidence of declines in wages with age after this point? b) Use the table above to test the hypothesis that the returns to higher education estimated in model (1) are 10%. c) Considering equation (2), what evidence do the estimates provide on the nature of returns to training? At what level of training are returns to training at their maximum? d) In what circumstances would the estimator of the returns to training you derived in
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WageEqQ_handout - B2) Consider the following wage equation...

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