(A)symmetric interaction between house prices, stock market and exchange rates using linear and nonlinear approach: the case of Iran

Abstract

PurposeThe purpose of this study was to investigate the dynamic interactive link between housing prices, stock market price and effective exchange rate in the Iranian economy for a monthly period from April, 2004, to March, 2019. In addition, for a more accurate analysis, three control and determinates variables including real interest rate, real GDP and FDI have been added to the base model.Design/methodology/approachFor this purpose, we will consider this issue by developing the study of Lean & Smyth (2014), Ali & Zaman (2017) and Coskun et al (2017) in the framework of ADRL and NARDL models. Also, this study analyzed the asymmetric/non-linear impact of stock market indexes and effective exchange rate on Iran’s housing inflation. Asymmetries imply to both positive and negative changes in the variables.FindingsThe results obtained from the ADRL and NARDL models suggest that the existence of cointegration relationship between housing market price and its determinants. From linear model, we found that the exchange rate and stock market price have a positive effect on the real estate inflation in the short run; this relationship is also confirmed in the long run. Other empirical results indicate that the GDP stimulates housing price in both long and short run cases, while FDI and real interest rate have an opposite effect. In addition, the results provided by the asymmetric model lead to the rejection of the null hypothesis of no co-integration between the variables. In addition, we found that the effect of stock price in the short and long term are asymmetric and there also is an asymmetric long-run effect of real exchange rate on the real estate price.Originality/valueFinally, to analyze the sensitivity, we entered two explanatory variables of inflation and money supply to the baseline equation. The finding represented that in both linear and nonlinear framework, a positive correlation between these two variables with housing prices have been proved.