Mortgage lenders are interested in determining borrower and loan factors that may lead to delin… Show more Mortgage lenders are interested in determining borrower and loan factors that may lead to delinquency or foreclosure. In the file lasvegas.dat are 1000 observations on mortgages for single-family homes in Las Vegas, Nevada, during 2008. The variable of interest is DELINQUENT, an indicator variable 1%u20444 1 if the borrower missed at least three payments (90 or more days late), but zero otherwise. Explanatory variables are LVR 1%u20444 the ratio of the loan amount to the value of the property; REF 1%u20444 1 if purpose of the loan was a %u2018%u2018refinance%u2019%u2019 and 1%u20444 0 if loan was for a purchase; INSUR 1%u20444 1 if mortgage carries mortgage insurance, zero otherwise; RATE 1%u20444 initial interest rate of the mortgage; AMOUNT 1%u20444 dollar value of mortgage (in $100,000); CREDIT 1%u20444 credit score, TERM 1%u20444 number of years between disbursement of the loan and the date it is expected to be fully repaid, ARM 1%u20444 1 if mortgage has an adjustable rate, and 1%u20444 0 if mortgage has a fixed rate. (a) Estimatethelinearprobability(regression)modelexplainingDELINQUENTas a function of the remaining variables. Are the signs of the estimated coefficients reasonable? (b) InterpretthecoefficientofINSUR.IfCREDITincreasesby50points,whatisthe estimated effect on the probability of a delinquent loan? (c) ComputethepredictedvalueofDELINQENTforthefinal(1000th)observation. Interpret this value. (d) Compute the predicted value of DELINQUENT for all 1000 observations. How many were less than zero? How many were greater than 1? Explain why such predictions are problematic. • Show less