Factors affecting housing prices with an environmental approach (Comparison of some developed and developing countries)

Abstract

Considering that housing as a shelter and place of residence, after food and clothing is one of the basic and basic needs of human beings and healthy and clean air is the most essential vital need of every human being to live, Therefore, the purpose of this study is to investigate and compare the effect of air pollution and macroeconomic variables on housing prices in some developed countries (including: Norway, Switzerland, Australia, Iceland, Denmark, USA, Japan and the Czech Republic) and developing (including: Turkey, Mexico, Brazil, China, Colombia, South Africa, Indonesia, India) and Iran. For this purpose, 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 housing price index. Model estimation was performed in developed and developing countries using panel data technique during the period 2017-2010 and in Iran using a self-explanatory technique with wide Nonlinear Autoregressive Distributed Lag Method (NARDL) approach during the period 1996-2017. Due to the fact that in Iran, the housing price index was available for different cities (and not the whole country), so instead of this index, the rent index was used and as a result, Iran was examined separately. 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 showed that air pollution has a negative effect on house prices by 30% in developed countries, while there is no significant link between air pollution and house prices in developing countries. In Iran, the results from model estimation showed that reducing air pollution leads to an increase in housing rents by 23%, and increasing air pollution leads to a decrease in housing rents by 36%. Estimates also show that in both groups of countries and Iran, per capita income is the most effective variable on price, but the effect of some variables (such as price index of consumer goods and services, exchange rate and interest rate) on housing prices in these countries the review has been different. In developed countries, exchange rates and in developing countries and Iran, liquidity had no significant effect on housing prices.The practical conclusion from the findings is that; although there is virtually no market for environmental benefits such as clean air and it is not traded directly, it is valuable, and this value becomes apparent when violated. For example, when some areas are prone to air pollution, people are willing to pay more but enjoy clean air. Therefore, these inconsistencies cause additional costs in the city, and if a policy is adopted based on which environmental standards are maintained in the city, additional costs will be avoided and the rent of residential houses will be adjusted.