Are regional house prices stationary in Iran? New evidence using Fourier quantile unit root test

Abstract

Purpose In the Iranian economy, investing in the housing market has been very important and beneficial for investors and households, because of inflationary environment, low real interest rates, underdeveloped financial and tax systems and economic sanctions. Hence, prediction of house prices is the main concern of housing market agents in the economy. The purpose of this paper is to test the stationary properties of Iran's provinces to improve the prediction of future housing prices. Design/methodology/approach In this paper, the authors have tested the stationary properties of 20 Iran’s province centers over the period from 1993 to 2017 using a novel Fourier quantile unit root test and conventional ordinary/generalized least squares (O/GLS) linear unit root/stationary tests. Findings According to conventional O/GLS linear unit root/stationary tests, most of the house prices series exhibit random walk behavior, whereas by applying the Fourier quantile unit root test, the null hypothesis of unit root is rejected for 15 out of 20 series. Other results indicated that house prices of cities responded differently to positive and negative shocks. Originality/value Previous studies only addressed conventional OLS or GLS linear unit root or stationary tests, but novel Fourier quantile unit root test was not used. New results were obtained based on this unit root test, that, as a priori knowledge, will help benefiting from the positive effects, or avoiding being victimized by the negative effects.