Bayesian Estimation of a Hedonic Price Function for the Uptown of Tehran

In this paper, we survey some effective factors affecting house prices in the uptown of Tehran city with using Bayesian econometric method. In this method, we use expert ideas as prior information which causes to effective and better estimations. In this paper, we use sell prices of 546 apartments in the uptown of Tehran in 2014, these data are collected from real estates. We assume sale price of house to be dependent on the size of apartment, age of apartment, having pool, sauna and sport salon in the form of dummy variables. Results of this paper reveal that by using informative prior, an increase in the square meter of apartment causes 14 million and 500 thousands tomans increase in the house price. In our sample, an increase in house's age will cause a decline of almost 75 million tomans in the house price. In our sample, an increase in the age of house in the uptown of Tehran decline of almost 350000 tomans in price of one square meter of house. Our estimation results reveal that having pool, sauna and sport salon in the apartment will cause an increase of 420 million tomans in the house price.