please i need help with the question 5. Answer all parts. Consider thefollowing
ID: 3361561 • Letter: P
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please i need help with the question 5.
Answer all parts. Consider thefollowing wage equation: Where lnw is individual i's log wage, edu measures individual i's years of completed education, and erp, easures individual i's years of experience, and femalej is a dummy variable indicating whether individual i is a female, ei is an unobserved error term. The R2 = 0.283. You estimate regression (1) on a sample of male and female workers in the their 30s and lving and working in the UK. The sample size is 453. You obtain the following estimates: ent 0.0112 0.0052 31 0.0721 0.00207 0.155 83 0.000293 0.0521 1. 5 marks Interpret each of the OLS estimates. 2. f6 merks/ Can you reject the hypothesis that education has a positive effect on wages? 3. f6 marks Test the hypothesis that being female has a statistically significant effect on wages 4. f6 manksj Can you reject the claim that the returns to experience are linear? Be explicit about the hypothesis that you need to test this question. 5. f5 marks Calculate the ceteris paribus effect of 5 extra years of schooling on wages. 6. 19 marksj Interpret the R2 of the regression and test the overall significance of the model. You now obtain data on these workers' scores on an achievement test and add this variable to the regression You estimate regressions (2) and (3) as follows: Where test is the worker's score on an achievemnt test (mcasured in percentile rank) administered as part of the sue You are given the following coefficient estimates with the R ofestimation for model (2 being 0.293: cient timate Sao 0.0032 0.02378 0.06834 0.1031 7. 10 morks Compare the standard error of in model (2) with that of model (1) and explain passible 8. ks/ Under which assnptions can you interpret the coefficient as the causal effect of education 9. . 8 markss the information provided about the estimates of regT88ians 2) and (3) s'fficient for you to 10. 8 marksy Is either one of the log wage regressions likely to provide a good indication of the cusal effect 11. /7 marks We now control for the seniority by adding the variable tenure to our multiple regression model. i reasons for this change. on wages? Be specific about the assumptiou and explain in words what it mcans. explain why the coetficient on education is different between regression (1) and regressn (2) of education on wages? Use the information above to construct part of your responsc. Where tenure is the number of years with the same employer. Use an F-test to test whether the inclusion of the addital variables has improved themodel, i.e. comparing model 4 with model 1 lruni = A+ 1edui +2ezpit 3erpf + 4.fernalei +/htest.it Astenureit ti The R from this regression is 0.360.Explanation / Answer
b1 = 0.0818
if we change x by 1 (unit), we’d expect our y variable to change by 1001 percent”
when edu is increased by 5 years
0.0818 *5 = 0.409
hence wage is increased by 100 * 0.409 % = 40.9 %
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