We fit a logit model to 2380 observations in our data set on mortgage denial (deny)...

 

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We fit a logit model to 2380 observations in our data set on mortgage denial (deny) and the payment-to-income ratio (P/I ratio). A logit regression of deny against P/I ratio and black yields the estimated regression function as follows. Pr (deny = 1|P/I ratio, black) F(-4.13 + 5.37* P/I_ratio + 1.27 * black) (0.35) (0.96) (0.15) = * Week 6 slide example 1) A black mortgage applicant has a P/I ratio of 0.35. What is the probability that his application will be denied ? * Week 6 slide example 2) Suppose that the applicant reduced this ratio to 0.30. What effect would this have on his probability of being denied a mortgage? a) Repeat Week 6 slide example 1) and 2) for a white applicant. b) Does the marginal effect of the P/I ratio on the probability of mortgage denial depend on race? Explain. c) Let's suppose that the model of mortgage denial regression model result shows the coefficient on black is 0.084. What is the implicit meaning of this coefficient? d) Think of an important omitted variable that might bias the answer of the logit regression model. In particular, what is it and how would it bias the results of c)? We fit a logit model to 2380 observations in our data set on mortgage denial (deny) and the payment-to-income ratio (P/I ratio). A logit regression of deny against P/I ratio and black yields the estimated regression function as follows. Pr (deny = 1|P/I ratio, black) F(-4.13 + 5.37* P/I_ratio + 1.27 * black) (0.35) (0.96) (0.15) = * Week 6 slide example 1) A black mortgage applicant has a P/I ratio of 0.35. What is the probability that his application will be denied ? * Week 6 slide example 2) Suppose that the applicant reduced this ratio to 0.30. What effect would this have on his probability of being denied a mortgage? a) Repeat Week 6 slide example 1) and 2) for a white applicant. b) Does the marginal effect of the P/I ratio on the probability of mortgage denial depend on race? Explain. c) Let's suppose that the model of mortgage denial regression model result shows the coefficient on black is 0.084. What is the implicit meaning of this coefficient? d) Think of an important omitted variable that might bias the answer of the logit regression model. In particular, what is it and how would it bias the results of c)?

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a For a white applicant with a PI ratio of 035 the probability that his application will be denied i... View the full answer