What impacts the formation of prices of apartments in Vasteras? : With a hedonic pricing model approach

Abstract: Determining and predicting the exact prices of apartments is a complex task. It requires the data on the factors that directly influence the price of the apartment, such as the number of rooms or location of the apartment, and the information about the factors that indirectly affect the price, such as the availability of public transport and public goods near the apartment. One of the limitations of our work is the lack of data on the availability of indirect factors, and so in this paper we purely focus, and determine to what extent direct factors influence the formation of the final price. We find the influence of each of these factors with the help of the hedonic pricing, and the method of linear regression. After the first regression we identified which variable is least significant for our work and removed it. In our case it happened to be the variable Floor that identifies the level of the apartment. Further, we also test other types of regressions, such as semi – log regression, double – log regression, and quadratic regression. This is done to identify which of the regressions demonstrates the clearest picture on the effects of the variables. In other words, in which of the regressions the variables have the most significant parameter values. We found the Regression Five, a quadratic regression, to be an equation with the most significant parameter values. We also identified that the variables Rooms (indicating the number of rooms in the apartments) and Share (indicating the corporate share in the building) to have the biggest impact on the formation of the final price. Thus, we conclude that the variables Rooms and Share have the most significant influence on the price, whereas a quadratic regression (in this paper Regression Five) presents an equation with the most significant values of parameters and the highest degree of explanation.