Question

I need help understanding how to interpret a linear regression using a Hedonic Model. I have a just of what it is but I am not conveying it correctly.

Here is the data I had to do a regression: B is Beta by the way

where P_H = price of the house ($) B1BEDS = bedrooms (number) B2BATHS = bathrooms (number)     B3SQFT = area of the house (feet squared) B4LOT = area of the lot (feet squared) B5DISTANCE = distance from the lake (feet) B6SECCHI = lake water clarity (meters) B7SURFCAREA = surface area of the lake (kilometers squared)

The question is

2. Provide numerical interpretations of the coefficient estimates for β₂, β₃, and β₆. So for B2 that is bath my coefficient from my regression is 35024.4971. How do I interpret this? I was saying for every increase in a bath the Marginal willingness to pay for it is 35024.4971. Just does not seem right :/. My B3 square footage was 96.6 again..I said for every increase in square footage the MWTP increases by 96.6. My B6 is 39,422 which is water clarity. Can someone please explain to me the correct interpretation for these coefficients when its using hedonic prices I'm confused.

Answer 1

In hedonic regression methods, heterogeneous goods can be described as a function of their attributes or characteristics. In your example, the housing context, these attributes or characteristics may contain both the structure of the asset and the location of the asset.
The hedonic method may be used for the purpose of obtaining the estimates of the willingness to pay for, or marginal cost of producing, the different characteristics.

The most popular specification of the model is the log-lin form
pi = exp(a+xb)
ln(p_it) = b₀ + b₁x + u_it

Your question does not specify the functional form, but it seems it is a fully linear form. That is also fine and the interpretations that you have made are also correct.

But, if we have the semi-log form, and b₂, b₃ and b₆ are the coefficients of number of bathrooms, area of the house, and the lake water clarity.
A unit change in the number of bathrooms will increase the price of the house by [exp(b₂) - 1] %
A unit change in the area of the house will increase the price of the house by [exp(b₃) - 1] %
A unit change in the clarity of water by a meter, will increase the marginal willingness to pay for clean water by [exp(b₆) - 1] %