Using 88 observations, a researcher constructs and econometric model to explain the housing price in a certain city:
Where price refers to the house price (in $1000s), assess is the assessed housing value (before the house was sold), lotsize is the size of lot in square feet, sqrft is the size of house in square feet and bdrms is the number of the bedrooms.
(a) Discuss the estimation output provided in the Table referring to all information you find relevant the explanation/determination of house prices in the city. For the significance test on each regressor’s coefficient use 10% significance level.
(b) Based on model (1) and the estimation output from Table 3, test at the respective level the following hypotheses:
i) 0 ∶ 2 = 0.01 . 1 ∶ 2 ≠ 0.01 at the 5% level
ii) 0 ∶ 4 = 0 . 1 ∶ 4 > 0 at the 10% level.
(c) Using information from Table 3 derive the explained sum of squares (SSE).
(d) Additional EVIEWS output is provided below. Use any additional information you find useful from Table 4 or Table 5 (not both) in order to test, at the 5% significance level, the joint restrictions on model (1) (whose estimation output is given in Table 4)