These parameters measure the proportional change in prices caused by proportional changes in characteristics. Here the parameters β1 to β5 are elasticities. This means that as a characteristic increases (or improves) the house prices increase but at a decreasing rate. Usually researchers estimating hedonic prices assume the hedonic price function has a multiplicative functional form. The hedonic price can therefore be interpreted as the additional cost of purchasing a house that is marginally ‘better’ in terms of a particular characteristic. The change in a house price resulting from the marginal change in one of these characteristics is called the hedonic price (sometimes referred to as the implicit price or rent differential). Where the price of a house (P), is a function of its location relative to a local urban centre (LOC), the type of house (TYPE), the size of the plot (SIZE), the quality of its view (VIEW), and neighbourhood characteristics (NEIGH) such as school quality and crime. For example, the price of a house can be summarised using a hedonic price function as below: The first step estimates the relationship between the price of an asset (the dependent variable) and all of its various characteristics (independent variables). The hedonic regression analysis is conducted in two steps.
Hedonic Regression Analysis (adapted from Boardman et al, 2001, 349-352) It may be found that a 1km movement away from the open cast site equates to an increase of £5,000 on a house price. The regression analysis can also be used to provide a value for the size of the relative impact. If, for example, through regression analyses increased distance from an open cast mining site is found to be correlated with increased house prices, it can be ascertained that the open cast site is having a negative impact on house prices. The hedonic price method is used to measure the relative importance – through use of regression analyses – of these independent ‘explanatory’ variables on house and property prices.
0 kommentar(er)
