Forecasting house prices in Iran using GMDH

Behrooz Nazemi and Mohsen Rafiean

International Journal of Housing Markets and Analysis, 2020, vol. 14, issue 3, 555-568

Abstract: Purpose - An accurate predictive model for forecasting urban housing price in Isfahan can be useful for sellers and owners to take more appropriate actions about housing supplying. Also, it can help urban housing planners and policymakers in managing of the housing market and preventing an urban housing crisis in Isfahan. The purpose of this paper is forecasting housing price in Isfahan city of Iran until 2022 using group method of data handling (GMDH). Design/methodology/approach - This paper presents an accurate predictive model by applying the GMDH algorithm by using GMDH-Shell software for forecasting housing price in municipal boroughs of Isfahan city till the second half of 2022 based on creating time series and existing data. Alongside housing price, some other affecting factors have been also considered to control the forecasting process and make it more accurate. Furthermore, this research shows the housing price changes of boroughs on map using ArcMap. Findings - Based on forecasting results, the housing price will increase at all boroughs of Isfahan till second half of the year 2022. Amongst them, Borough 15 will have the highest percentage of the price increasing (28.27%) to year 2022 and Borough 6 will have the lowest percentage of the price increasing (8.34%) to the year 2022. About ranking of the boroughs in terms of housing price, Borough number 6 and 3 will keep their current position at the top and Borough number 15 will stay at the bottom. Research limitations/implications - In this research, just few factors have been selected alongside housing price to control the forecasting process owing to limitation of reliable data availability about affecting factors. Originality/value - The most remarkable point of this paper is reaching to a mathematical formula that can accurately forecast housing price in Isfahan city which has been rarely investigated in former studies, especially in simplified form. The technique used in this paper to forecast housing price in Isfahan city of Iran can be useful for other cities too.

Keywords: Forecasting; GIS; Algorithm; Housing price; Analyzing; GMDH (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.emerald.com/insight/content/doi/10.110 ... d&utm_campaign=repec (text/html)
https://www.emerald.com/insight/content/doi/10.110 ... d&utm_campaign=repec (application/pdf)
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eme:ijhmap:ijhma-05-2020-0067

DOI: 10.1108/IJHMA-05-2020-0067

Access Statistics for this article

International Journal of Housing Markets and Analysis is currently edited by Dr Richard Reed

More articles in International Journal of Housing Markets and Analysis from Emerald Group Publishing Limited
Bibliographic data for series maintained by Emerald Support ().