Applied Econometrics, please provide detailed solutions and i will give you thumbs up!

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(a) A labour economist is interested in the factors that affect wages of individuals. She collects data from 2060 individuals and runs a regression using OLS. The results are shown below: Source SS df MS Model Residual 73.3672853 286.087029 6 2053 12.2278809 .139350721 Number of obs = FC 6, 2053) = Prob > F R-squared Adj R-squared Root MSE 2060 87.75 0.0000 0.2041 0.2018 .3733 Total 359.454315 2059 . 174577132 Lnwage Coef. Std. Err. t P>t LnIQ educ married black exper expersa _cons 3324731 .0694675 -.0255137 -.1199325 .0859623 -.0024365 3.387865 .0657472 .004915 .0042279 .0263364 .00977 .0005003 .2994325 5.06 14.13 -6.03 -4.55 8.80 -4.87 11.31 0.000 0.000 0.000 0.000 0.000 0.000 0.000 [95% conf. Interval] 2035349 .4614113 .0598287 .0791064 -.0338051 -.0172222 -.1715813 - .0682837 .0668022 . 1051225 -.0034176 -.0014554 2.800642 3.975088 Note: "Ln" stands for natural logarithm The variables used in the model are defined as follows: wage IQ educ married black exper expersa = Hourly wage (in $) = IQ score = Years of schooling = Variable taking value 1 if the individual is married, 0 otherwise = Variable taking value 1 if the individual is black, 0 otherwise = Work experience in years) = Square of variable exper i. Interpret the above results, paying careful attention to the signs, magnitudes and statistical significance of the coefficients. ii. Calculate the predicted wage of a white married individual. This person has 12 years of education and 8 years of work experience with an IQ score of 93. iii. In the above model, what is the purpose of introducing the variable "exper" alongside the variable "expersq? Perform appropriate calculations to explain what information can be obtained from the estimated coefficient on these variables. (b) Explain the term serial correlation and describe two tests for detecting it