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1 - [50pts] Using cross-sectional data on individuals, regression estimated logarithm of the average hourly wage measured in dollars (log(Salary)) over the years of study

1 - [50pts] Using cross-sectional data on individuals, regression estimated logarithm of the average hourly wage measured in dollars (log(Salary)) over the years of study (Educ), years of professional experience (Exper) and years at current employer (Anc) is as follows log(Salary) = 0.248 + 0.092 Educ + 0.004 Exper + 0.022 Anc, (0.104) (0.007) (0.002) (0.003) 526. R? = 0.316 and SCR = 101.46 Al CIF not where the streamed types appear in parentheses below the parameter estimates of the regression model and SCR denote the sum of the squares of the residuals. To calculate the critical values, note that P(Z > 1.96) = 0.025 when Z ~ Normal(0.1). (a) [10] Interpret the estimate of the coefficient associated with Educ. Is this coefficient statis- Critically significant at the 5% significance level? (b) [7.5] For a given level of education, what is the approximate average increase estimated as a percentage of the hourly wage associated with an employee working an additional year extra with his current employer? (c) [5] Are there any other factors which may influence log(Salary) and which are omitted in this regression? If yes, give an example. Are these factors likely to be correlated with the explanatory variables of this regression? Why ? D) according to your answer in (c) do the OLS estimators of this regression have a causal interpretation? Explain your answer. (0) 15) Quo menu the determination coaticle At 7 Interpret the result. he = O. 16. (D) (7.5) The sum of the carts of the rtidius of the regression of log(Salary) on a con stante and Educ is teale at 190 77. Vilive this value to verify if the coetracts of Exper and Anc are statistically sienicatits at the 6% significance level. (Index (1) F = SCR-SCRu.)(9 (i) Use critical value 3.00.) SCRae/(n-k-1) (8) (10) Let Experm = 12Exper be a variable that measures experience in months rather only in years. Using the same sample, consider the regression of log(Salary) on a constant, Educ, Experm, and Anc. What would be the slope coefficients of Educ and Experienced? Explain your answer.

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