1. A researcher is studying the effect of parents' level of education on educational achievement of...

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1. A researcher is studying the effect of parents' level of education on educational achievement of individuals. Using data on completed years of education (educ), mother's level of education (motheduc), father's level of education (fatheduc), a measure of cognitive ability (abil), and logarithm of family income (1.income), the researcher estimates 4 models. Table (1) shows the OLS estimates for each model, with standard errors in parentheses underneath each coefficient. The dependent variable in all the models is educ. Model 2 Model 3 Model 4 Independent variables l.income motheduc fatheduc abil abil_squared Intercept N SSR R-squared Model 1 0.27 (0.02) 0.53 (0.03) 6.94 (0.32) 1230 3999.24 0.35 0.18 (0.03) 0.11 (0.02) 0.52 (0.03) 8.4 (0.12) 1230 3899.97 0.38 0.17 (0.03) 0.11 (0.02) 0.39 (0.03) 0.05 (0.01) 8.74 (0.31) 1230 3785.24 0.45 5 (0.2) 0.15 (0.03) 0.10 (0.02) 0.35 (0.03) 0.09 (0.01) 8.74 (0.31) 1210 3541.2 0.49 Table (1) a. Interpret the R-squared of the regression in model 1. [5 marks] b. Can you reject the claim that the returns to ability are linear? Be explicit about the hypothesis and any assumptions you make in order to answer the question. c. Carefully interpret the effect of increasing of l.income by 10. d. How the degrees of freedom in model (3) compare to the degrees of freedom in model (4)? Explain. [5 marks] [6 marks] [6 marks] e. Why did the coefficient of motheduc decrease after adding variable fatheduc to the regression? Discuss and if necessary, incorporate the Gauss-Markov assumptions in [8 marks] your answer. 1. A researcher is studying the effect of parents' level of education on educational achievement of individuals. Using data on completed years of education (educ), mother's level of education (motheduc), father's level of education (fatheduc), a measure of cognitive ability (abil), and logarithm of family income (1.income), the researcher estimates 4 models. Table (1) shows the OLS estimates for each model, with standard errors in parentheses underneath each coefficient. The dependent variable in all the models is educ. Model 2 Model 3 Model 4 Independent variables l.income motheduc fatheduc abil abil_squared Intercept N SSR R-squared Model 1 0.27 (0.02) 0.53 (0.03) 6.94 (0.32) 1230 3999.24 0.35 0.18 (0.03) 0.11 (0.02) 0.52 (0.03) 8.4 (0.12) 1230 3899.97 0.38 0.17 (0.03) 0.11 (0.02) 0.39 (0.03) 0.05 (0.01) 8.74 (0.31) 1230 3785.24 0.45 5 (0.2) 0.15 (0.03) 0.10 (0.02) 0.35 (0.03) 0.09 (0.01) 8.74 (0.31) 1210 3541.2 0.49 Table (1) a. Interpret the R-squared of the regression in model 1. [5 marks] b. Can you reject the claim that the returns to ability are linear? Be explicit about the hypothesis and any assumptions you make in order to answer the question. c. Carefully interpret the effect of increasing of l.income by 10. d. How the degrees of freedom in model (3) compare to the degrees of freedom in model (4)? Explain. [5 marks] [6 marks] [6 marks] e. Why did the coefficient of motheduc decrease after adding variable fatheduc to the regression? Discuss and if necessary, incorporate the Gauss-Markov assumptions in [8 marks] your answer.

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a The Rsquared of the regression in model 1 is 035 indicating that approximately 35 of the variabili... View the full answer