Spatial analysis of housing prices in Tehran city

Abstract

Purpose The purpose of this study is to identify the situation of spatial inequality in the residential system of Tehran city in terms of housing prices in the year 2021 and to examine its changes over time (1991–2021). Design/methodology/approach In terms of purpose, this study is applied research and has used a descriptive-analytical method. The statistical population of this research is the residential units in Tehran city 2021. The average per square meter of a residential unit in the level of city neighborhoods was entered in the geographical information system (GIS) in 2021. Moran’s spatial autocorrelation method, map cluster analysis (hot and cold spots) and Kriging interpolation have been used for spatial analysis of points. Then, the change in spatial inequality in the residential system of Tehran city has been studied and measured based on the price per square meter of a residential unit for 30 years in the 22 districts of Tehran by using statistical clustering based on distance with standard deviation. Findings The result of spatial autocorrelation analysis with a score of 0.873872 and a p-value equal to 0.000000 indicates a cluster distribution of housing prices throughout the city. The results of hot spots show that the highest concentration of hot spots (the highest price) is in the northern part of the city, and the highest concentration of cold spots (the lowest price) is in the southern part of Tehran city. Calculating the area and estimating the quantitative values of data-free points by the use of the Kriging interpolation method indicates that 9.95% of Tehran’s area has a price of less than US$800, 17.68% of it has a price of US$800 to US$1,200, 25.40% has the price of US$1,200 to US$1,600, 17.61% has the price of US$1,600 to US$2,000, 9.54% has the price of US$2,000 to US$2,200, 6.69% has the price of US$2,200 to US$2,600, 5.38% has the price of US$2,600 to US$2,800, 4.59% has the price of US$2,800 to US$3,200 and finally, the 3.16% has a price more than US$3,200. The highest price concentration (above US$3,200) is in five neighborhoods (Zafaranieh, Mahmoudieh, Tajrish, Bagh-Ferdows and Hesar Bou-Ali). The findings from the study of changes in housing prices in the period (1991–2021) indicate that the southern part of Tehran has grown slightly compared to the average range, and the western part of Tehran, which includes the 21st and 22nd regions with much more growth than the average price. Originality/value There is massive inequality in housing prices in different areas and neighborhoods of Tehran city in 2021. In the period under study, spatial inequality in the residential system of Tehran intensified. The considerable increase in housing prices in the housing market of Tehran has made this sector a commodity, intensifying the inequality between owners and non-owners. This increase in housing price inequality has caused an increase in the informal living for the population of the southern part. This population is experiencing a living situation that contrasts with the urban plans and policies.

Teheránban lakni

“…-A város legmagasabb presztízsű lakóterületei jellemzően az Alborz lábához legközelebb eső -vagyis legmagasabban fekvő, így leginkább élhető klímájú -1., 2. és 3. kerületekben helyezkednek el. [4] Itt a legmagasabbak az ingatlanárak, de ennek ellenére itt is folyamatos a város fejlődése, terjeszkedése. A Shahid Mahallati negyed Teherán 1. kerületében, a Shemiranat szomszédságában található északkeleti városrészek egyike.…”

“…Az Isar 11 lakóház északi homlokzata (fotó: Farzin Fereidouni) 07Bejárati részlet (fotó: Farzin Fereidouni) 08Teherán kerületei és az ingatlanárak emelkedése észak felé az Isar 11 lakóház helyével[4] központi fennsíkjáról származó, könnyen hozzáférhető agyagból égetett, jó minőségű tégla a történeti épületeken használt szerkezeti funkcióján túl a kortárs iráni építészetben új funkciót talált magának: mivel az iráni épület-díszítőművészetre korábban is jellemző volt a mázas kerámia használata, ennek a hagyománynak a folytatásaként a helyi kortárs építészetben a tégla mint homlokzati elem felértékelődik és a geometrikus téglamotívumok alkalmazásával önmagában válik a homlokzat díszévé [5]. Ez a tendencia jól látható Teherán mai arculatában.…”

Network analysis of comovements among newly-built residential house price indices of seventy Chinese cities

“…For economic analysis regarding the real estate sector, many efforts have been devoted to research on price relations (Li and Li, 2022; Hosseini et al , 2022). Fundamental time-series models, such as the VAR and VECM, and different varieties of their variations have been applied widely to perform such analysis (Vishwakarma, 2021; Ji and Bhandari, 2022; Squires et al , 2022).…”