Introductory Econometrics: A Modern Approach 6th Edition by Jeffrey M Wooldridge

Exercise 15

Use the data in HPRICE1.RAW for this exercise.

(i) Estimate the model

price = ????0 + ????1lotsize + ????2sqrft + ????3bdrms + u

and report the results in the usual form, including the standard error of the regression. Obtain predicted price, when we plug in lotsize = 10,000, sqrft = 2,300, and bdrms = 4; round this price to the nearest dollar.

(ii) Run a regression that allows you to put a 95% confidence interval around the predicted value in part (i). Note that your prediction will differ somewhat due to rounding error.

(iii) Let price0 be the unknown future selling price of the house with the characteristicsused in parts (i) and (ii). Find a 95% CI for price0 and comment on the width of this confidence interval.

Step 1 of 8

Consider the provided HPRICE1.RAW to solve the subparts.

(i)

Let “Price” be the dependent variable and “Lotsize”, “Sqrft”, and “Bdrms” be the explanatory variables. The multiple linear regression model is:

Here, the intercept is the predicted value of when are equal to zero andare the slope coefficients. To estimate the model, use Minitab software, the regression model is shown below: