19 Jun HOW MANY VARIABLES ARE ON THE RIGHT-HAND SIDE OF THE AUXILIARY REGRESSION?
Step 1: Use the Data to estimate the Model with OLS Use lnpricei as the dependent variable and use all the other variables in Table 10.3 as independent variables in your regression. 1. Which variables have coefficients that are significant in the expected direction at the 5-percent level? 2. Explain the meaning of all the estimated slope coefficients. Step 2: Multicollinearity Concerns 1. Could severe imperfect multicollinearity account for any of the coefficients being insignificant at the 5-percent level? 2. If so, which ones? Use simple correlation coefficients and VIFs to support your answer. Step 3: Heteroskedasticity Concerns 1. Plot the residuals from your OLS regression against the passenger capacity. 2. Do the residuals look heteroskedastic? Explain. Step 4: Conduct a Breusch–Pagan Test for Heteroskedasticity Use all the right-hand variables in the original model to run the Breusch– Pagan auxiliary regression. Write the null and alternative hypotheses, compute the test statistic, and conduct the test at the 5-percent level. Does heteroskedasticity appear to be present? Step 5: Conduct a White test for heteroskedasticity Test the regression in Step 1 at the 5-percent level for heteroskedasticity using the White test. Use the White test command in your regression package to run the auxiliary regression and to calculate the test statistic. 1. How many variables are on the right-hand side of the auxiliary regression? 2. What is the chi-square critical value? 3. According to the White test, does there appear to be heteroskedasticity in the model?
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