University of Isfahan Urban Economics 2588-4867 6 1 2021 04 21 Analyzing the Spread of Housing Price Shocks across Tehran City’s Regions Using Network Approach Analyzing the Spread of Housing Price Shocks across Tehran City’s Regions Using Network Approach 127 144 27964 10.22108/ue.2023.137878.1261 FA Hojatollah Mirzaei Assistant Professor, Department of Economics, Allameh Tabatabai University of Tehran, Iran Narges Razban Ph.D. Student, Department of Economics, Allameh Tabatabai University of Tehran, Iran Teamor Mohamadi Professor, Department of Economics, Allameh Tabatabai University of Tehran, Iran Habibollah Morovat Associate Professor, Department of Economics, Allameh Tabatabai University of Tehran, Iran 0000-0003-4291-1581 Journal Article 2023 06 02 The housing price as an important variable in the housing market is of major economic and social importance. Basically, “whether the trend of housing prices in one region can influence the price trends in other regions”, is an important problem. This suggests that there is a lead-lag relationship between prices in different areas, in which price fluctuations in one area lead to similar price movements in other areas. That is known as the wave or southeast effect in housing economy literature. In this research, the housing price network between 22 districts of Tehran city has been investigated with the help of the VAR model during the period from March 2009 to March 2022 in the form of 4 urban blocks. The housing network is analyzed based on the variance analysis of the prediction error obtained from the VAR model both for the entire period and dynamically. (1) The research results show that regions 2, 5, 14, and 10 are the strongest senders of price shocks among the 22 regions. (2) Regions 1, 8, 11, and 18 are the biggest receivers of the housing price shock. (3) The strongest housing network related to the block includes areas 4, 5, 8, 13, 20, and 21. (4) The housing price shock in the years 2017-2018 had the greatest effect on the price of the same region in the following period so the density of the housing price network has decreased during this period. Furthermore, the results show that the increase in housing prices in the years 2020-2021 did not have a significant impact on the housing network of the regions. The housing price as an important variable in the housing market is of major economic and social importance. Basically, “whether the trend of housing prices in one region can influence the price trends in other regions”, is an important problem. This suggests that there is a lead-lag relationship between prices in different areas, in which price fluctuations in one area lead to similar price movements in other areas. That is known as the wave or southeast effect in housing economy literature. In this research, the housing price network between 22 districts of Tehran city has been investigated with the help of the VAR model during the period from March 2009 to March 2022 in the form of 4 urban blocks. The housing network is analyzed based on the variance analysis of the prediction error obtained from the VAR model both for the entire period and dynamically. (1) The research results show that regions 2, 5, 14, and 10 are the strongest senders of price shocks among the 22 regions. (2) Regions 1, 8, 11, and 18 are the biggest receivers of the housing price shock. (3) The strongest housing network related to the block includes areas 4, 5, 8, 13, 20, and 21. (4) The housing price shock in the years 2017-2018 had the greatest effect on the price of the same region in the following period so the density of the housing price network has decreased during this period. Furthermore, the results show that the increase in housing prices in the years 2020-2021 did not have a significant impact on the housing network of the regions. https://ue.ui.ac.ir/article_27964_87b7c48b206022d1f10a28e4cb626511.pdf