International Journal of Nonlinear Analysis and Applications

Analysis of the asymmetric effect of air pollution on housing prices in Iran (using the NARDL approach)

Document Type : Research Paper

Authors

1 Department of Economics, Faculty of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Iran

2 Faculty of Economics, Allameh Tabatabaei University, Tehran, Iran

Abstract

Given the expansion of cities in recent decades, it is necessary to address environmental problems such as air pollution and study its impact on the economy. One of the most important sectors of the economy in which the environmental effects are very evident is the housing sector. The importance of housing is such that has always been introduced as one of the main human needs. However, the increase in housing prices in recent years and the high cost of services, in the housing sector, have led to little attention being paid to consumer tastes and preferences, including clean air, in housing construction. Therefore, considering the importance of air and housing pollution, the purpose of this article is the asymmetric analysis of the effect of air pollution on the housing price index in Iran. In this regard, the macroeconomic model was used in which the variables of air pollution index, per capita income, liquidity, consumer price index, interest rate and exchange rate were used as explanatory variables for the dependent variable of the housing rent index. The model was estimated using annual data over a period of time (1996-2017) for the Iranian economy and using the Nonlinear Autoregressive Distributed Lag Method (NARDL). The NARDL technique is able to examine the effect of positive and negative air pollution shocks in the short and long term separately on housing prices. It should be noted that the indicator used to express air pollution is (PM2.5). The results of the estimate indicate the fact that each negative shock of air pollution leads to an increase in rent and each positive shock of air pollution leads to a decrease in rent. Estimates also show that per capita income is the most effective variable on housing prices, while interest rate and liquidity had no significant effect on housing prices.

Keywords

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International Journal of Nonlinear Analysis and Applications
Volume 14, Issue 7
July 2023
Pages 233-242
  • Receive Date: 05 August 2022
  • Revise Date: 25 September 2022
  • Accept Date: 13 October 2022