Question

You are interested in studying the relationship between a home’s selling price and various features of the home (this is called a hedonic price analysis). You estimate the following regression equation, in thousands of dollars:
  
(house price) ̂=175+12bedroom+.8square_footage - 2.5distance

Where bedroom measures the number of bedrooms in the house, square_footage is the house’s square footage, measured in hundreds (e.g. 2,200 square foot house would enter the regression as 22), and distance is the distance from downtown, measured in miles.

a. Do the signs of the coefficients match your a priori expectations? Explain why or why not based on your intuition.

b. Suppose you are a realtor. Use the regression results to estimate the value of a client’s home with the following characteristics: 3,200 square feet; 4 bedrooms; located 6 miles from downtown.
  
c. How would your estimate change if the client decided to add a 200 square-foot bedroom?

Answer 1

(a)

The signs of the coefficients matches our a priori expectations.

Explanation:

The coefficient of bedroom = 12 is positive. This matches our a priori expectations because as the number of bed rooms increases, house price will increase.

The coefficient of square - footage = 12 is positive. This matches our a priori expectations because as the square - footage   increases, house price will increase.

The coefficient of distance = - 2.5 is negative. This matches our a priori expectations because as the distance from downtown increases, house price will decrease.

(b)

For

square-footage = 32, bedroom = 4, distance = 6:

Substituting we get:

(house price) = 175 +(12 X 4) + (8 X 32) - (2.5 X 6)

                  = 175 + 48 + 256 - 15

                = 464

Value of a client's home= $464,000

.(c)

For

square-footage = 34, bedroom = 4, distance = 6:

Substituting we get:

(house price) = 175 +(12 X 4) + (8 X 34) - (2.5 X 6)

                  = 175 + 48 + 272 - 15

                = 480

Increase = 480 - 464 = 16

Value of a client's home will increase by = $16,000

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