A major national supplier of building materials for residential construction is concerned about total sales for next year. It is well known that the company's sales are directly related to the total national residential investment. Several New York bankers are predicting that interest rates will rise about two percentage points next year. You have been asked to develop a regression analysis that can be used to predict the effect of interest rate changes on residential investment. In addition to interest rate, you believe that the GDP, money supply, government spending, and price index for finished goods might be predictors of residential investment. Therefore, you decide that two multiple regression models will be needed. One will include prime interest rate and important additional variables. The second will include federal funds interest rate and important additional variables. The time-series data for this study are contained in the data file named Macro2010, which is described in the Chapter 13 appendix.
a. Develop two multiple regression models to predict residential investment using prime interest rate for one and federal funds interest rate for the other. The final regression models should include only predictor variables that have a significant conditional effect. Analyze the regression statistics and indicate which equation provides the best predictions.
b. Determine the 95% confidence interval for the interest rate conditional slope coefficient in both regression equations.