An econometric panel data‐based approach for housing price forecasting in Iran

Abstract

Purpose

The purpose of this paper is to estimate long‐run elasticities for housing prices in Tehran's (capital of Iran) 20 different zones relative to several explanatory variables available for use such as land price, total substructure area, material price, etc. Moreover, another goal of this paper is to propose a new approach to deal with problems which arise due to a lack of proper data.

Design/methodology/approach

The data set is gathered from “The Municipality of Tehran” and “The Central Bank of Islamic Republic of Iran (CBI)”. One‐way fixed effects and one‐way random effects approaches (which are panel data approaches) are applied to model housing price forecasting function in Tehran's 20 different zones. Results are compared with ordinary least squares approach which is a common approach in this field. Finally, outcomes of the preferred approach are discussed and analyzed with regard to the economic point of view.

Findings

Results show that one‐way fixed effects approach provides more accurate forecasts and can be considered as a suitable tool to deal with housing price forecasting problems in environments which are: uncertain, complex, and faced with a lack of proper data. Moreover, it is found that land price is the most effective factor that has impact on total housing cost in Tehran, i.e. the main portion of house prices in Tehran is affected by land price, so appropriate policies have to be made by the government to control fluctuations of this factor.

Practical implications

The proposed approach will supply policy makers with improved estimations with decreased errors in uncertain and complex environments which are faced with a lack of proper data, and it extracts valuable information which enables policy makers for handling non‐linearity, complexity, as well as uncertainty that may exist in actual data sets with respect to housing price forecasting. Moreover, the proposed approach can be applied to similar housing price case studies to obtain more accurate and more reliable outcomes.

Originality/value

Applying panel data approach for estimation of housing prices is relatively new in the field of housing economics. Moreover, this is the first study which employs panel data approach for analyzing the housing market in Tehran.

Citation

Hadavandi, E., Ghanbari, A., Mohsen Mirjani, S. and Abbasian, S. (2011), "An econometric panel data‐based approach for housing price forecasting in Iran", International Journal of Housing Markets and Analysis, Vol. 4 No. 1, pp. 70-83. https://doi.org/10.1108/17538271111111848