2. Now, reestimate the model using the log of netinc and salary: return = -36.30 + .327dkr + .069eps - 4.74log(netinc) + 7.24log(salary) (39.37) (.203) (.080) (3.39) (6.31) n = 142 R2 = .0330 %3D Do any of your conclusions from part (1.) change?
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- In a recent closely contested lawsuit, Apex sued Bpex for patent infringement. The jury came back today with its decision. The rate o return on Apex was rA = 3.7%. The rate of return on Bpex was only rg = 3.3%. The market today responded to very encouraging new about the unemployment rate, and M = 3.4%. The historical relationship between returns on these stocks and the market portfolio has been estimated from index model regressions as: Apex: A = 0.3% + 1.5PM Bpex: rg = -0.1% + 0.5rM. Required: a. What is the predicted returns for Apex & Bpex? b. Which company do you think won the lawsuit? Complete this question by entering your answers in the tabs below. Required A Required B What is the predicted returns for Apex & Bpex? Note: Do not round intermediate calculations. Round your answers to 1 decimal place. Apex Врех Predicted Returns % %Suppose you regress the annual percentage stock price returns on Russell 2000 small cap index for on a the percentage annual returns for a market index. Use the following output from this linear regression to answer questions a. - f. a. What is the formula for the Russell 2000's characteristic line? b. You forecast a market return of 6% next year. According to the market model, what is next year's expected return for the Russell 2000 index? c. What is the correlation between the return on the Russell 2000 and the return on the market Index? d. How much of the variation in the Russell 2000's returns are explained by the model? e. Based on these regression results, the Russell 2000 index would be considered what kind of an investment, defensive, aggressive, or market neutral? f. Does this regression have much explanatory power? Why or why not?Styles 6. The following two regression models are Probit and Logit respectively: Pr(Y=1|X)=(Bo+Bi xXr+Bzx X2) Pr(Y=1|X)=F(Bu + B₁ × Xs + B₂ × X2) (a) what functions do and F represent? (b) How do Probit, and Logit ensure that the predicted probabilities are always between 0 and 1? (c) Sketch a graph of the Y= $(Z) function. (Z on the horizontal axis, Y on the vertical axis) (d) What estimation method is used to estimate the coefficients in a Probit/Logit model? (e) What are the two measures of fit for models with binary dependent variables? Focus 88 B E
- Suppose you run the following regression: outcome=alpha0 + alpha1*female + alpha2*married + epsilon. You know that female equals 1 for females and 0 otherwise. You know that married equals 1 if the person is married and 0 otherwise. What is the estimated outcome for married females?Suppose you run the following regression: outcome=alpha0 + alpha1*female + alpha2*married + epsilon. You know that female equals 1 for females and 0 otherwise. You know that married equals 1 if the person is married and 0 otherwise. What is the estimated outcome for non-married females?Introductory Econometris: A Modern Approach 4th edition, Chapter 17 Problem 1CE: What is the command in R in order to run the "White heteroskedasticity-consistent standard errors & covariance"? In other words, I would like to run the new regression with robust standard errors in it.
- In a recent closely contested lawsuit, Apex sued Bpex for patent infringement. The jury came back today with its decision. The rate of return on Apex was A = 3.7%. The rate of return on Bpex was only rg = 3.3%. The market today responded to very encouraging news about the unemployment rate, and = 3.4%. The historical relationship between returns on these stocks and the market portfolio has been estimated from index model regressions as: Apex: A = 0.38 + 1.5M Bpex: rg-0.1% +0.51M a. What is the predicted returns for Apex & Bpex? (Do not round intermediate calculations. Round your answers to 1 decimal place.) Apex Bpex Predicted Returns % % b. Which company do you think won the lawsuit? O Apex O BpexExplain carefully why running the regression above might suffer from endogeneity concerns: are their any unobservable variables that might confound the results? Should we be worried about reverse causality? What empirical methods could we use to address these concerns?A potential customer has described the following scenario to you:We need to keep track of the data that our manufacturing firm needs to run smoothly.We make a number of products, each of which is manufactured by a different de-partment. Products are made up of a number of parts. Parts are bought fromsuppliers.You have been asked to perform a preliminary analysis of the scenario:a) Identify four sets of values from the scenario. b) Identify three relations from the scenario. c) Draw an entity-relationship diagram to visualise the sets and relations you have identi-fied. d) Use the relations you identified in part b) to define the following:i) A relation that records the parts that a department needs. ii) A relation that records the suppliers that a department deals with
- How Regression models are used for Forecasting purpose?2 In the simple linear regression model y = Bo + Bjx + u, suppose that E(u) + 0. Letting a, = E(u), show that the model can always be rewritten with the same slope, but a new intercept and error, where the new error has a zero expected value. 3 The following table contains the ACT scores and the GPA (grade point average) for eight college stu- dents. Grade point average is based on a four-point scale and has been rounded to one digit after the decimal. Student GPA ACT 1 2.8 21 2 3.4 24 3 3.0 26 4 3.5 27 3.6 29 6 3.0 25 7 2.7 25 3.7 30 (i) Estimate the relationship between GPA and ACT using OLS; that is, obtain the intercept and slope estimates in the equation GPA = B, + B¡ACT. Comment on the direction of the relationship. Does the intercept have a useful interpretation here? Explain. How much higher is the GPA predicted to be if the ACT score is increased by five points? (ii) Compute the fitted values and residuals for each observation, and verify that the residuals (approximately) sum…Explain why in every econometric model there must be an error term, explain its function.