- Could You Help To Answer F And G Please 1 (766.96 KiB) Viewed 32 times
could you help to answer f and g, please?
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answerhappygod
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could you help to answer f and g, please?
could you help to answer f and g, please?
sav; = Bo + Biinci + ui, Ui = Jinc; xei (1) where sav; is saving, inc; is income, Ej is a random variable with E(ei) = 0 and var(ei) = 02, where o is a constant. Assume that E¡ is independent of inci. Highlights and Notes a) (2 points) Are u; and inc; independent? Why? b) (3 points) Show that OLS Assumption 1 is satisfied in this question, i.e., E(ui|inci) = 0) c) (3 points) Calculate var(11;|inci) and show that the error term u is heteroskedastic, i.e., var(1;\inci) is not a constant. d) (3 points) Based on your calculation of part (b), can you conclude that the variance of savings increases with income? e) (3 points) Suppose that OLS Assumptions 2 and 3 are also satisfied. Then you run a regression of savings on income. Is your OLS estimator unbiased? consistent? efficient? Explain briefly. f) (2 points) Someone suggests transforming the regression by dividing Jinc; on both sides: SaVi = Bo- Jinci + B1 Jinc; + ei Jinci (2) sav; That is, run a regression of Vinc on and Jinc;. Show that OLS Assumption 1 is also elel E Vinci = 0 satisfied in this equation, i.e., inc; g) (4 points) You can run a regression either based on equation (1) or equation (2), which one do you prefer? Why? You only need to provide an intuitive answer.
sav; = Bo + Biinci + ui, Ui = Jinc; xei (1) where sav; is saving, inc; is income, Ej is a random variable with E(ei) = 0 and var(ei) = 02, where o is a constant. Assume that E¡ is independent of inci. Highlights and Notes a) (2 points) Are u; and inc; independent? Why? b) (3 points) Show that OLS Assumption 1 is satisfied in this question, i.e., E(ui|inci) = 0) c) (3 points) Calculate var(11;|inci) and show that the error term u is heteroskedastic, i.e., var(1;\inci) is not a constant. d) (3 points) Based on your calculation of part (b), can you conclude that the variance of savings increases with income? e) (3 points) Suppose that OLS Assumptions 2 and 3 are also satisfied. Then you run a regression of savings on income. Is your OLS estimator unbiased? consistent? efficient? Explain briefly. f) (2 points) Someone suggests transforming the regression by dividing Jinc; on both sides: SaVi = Bo- Jinci + B1 Jinc; + ei Jinci (2) sav; That is, run a regression of Vinc on and Jinc;. Show that OLS Assumption 1 is also elel E Vinci = 0 satisfied in this equation, i.e., inc; g) (4 points) You can run a regression either based on equation (1) or equation (2), which one do you prefer? Why? You only need to provide an intuitive answer.
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