House Price Forecast Model: Case of Vietnam Housing Market

Nguyen Tai Quang Dinh, Dang Bich Ngoc and Ngo Thu Giang ()
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Nguyen Tai Quang Dinh: Hanoi University of Science and Technology, School of Applied Mathematics and Informatics
Dang Bich Ngoc: University of Lincoln, School of Business
Ngo Thu Giang: Hanoi University of Science and Technology, School of Economics and Management

A chapter in Proceedings of the 11th International Conference on Emerging Challenges: Smart Business and Digital Economy 2023 (ICECH 2023), 2023, pp 345-358 from Springer

Abstract: Abstract Purpose – The purpose of this study is to build up a comprehensive model for house price forecast in Vietnam Housing market. Design/methodology/approach – The data related to house price; macro economic indicators and housing industry were gathered from www.euromonitor.com which is source of data for market and industrial researches. The study reviewed house price forecasting models with different forecast techniques from pass research papers. In results, a new house price forecasting model with a suitable forecasting technique is proposed. Findings – The results are obtained from the application of different forecasting techniques. The final model is confirmed based on the models’ error consideration. The forecast value is also determined basing on the selected model and forecasting techniques. Two proposed models are ARIMA and VAR. With the ARIMA model, the study comes up the conclusion that the housing price index has a dependent relationship depending on the value of that index over the past 2 years. With VAR model, the research found out that Urban population Ratio has an impact on housing price value for 3 consecutive years; and Housing Completions Index has a strong impact on the housing price index. Remarkably, the use of VAR models can bring positive results as well as more accurate forecasts in forecasting housing prices. Practical implications – The project of building a housing price forecast model in the real estate market in Vietnam. Therefore, the research results are important for investors in the housing market, suppliers, and policy makers in all fields from economics, finance and specifically in the real estate market in Vietnam.

Keywords: – Housing market; House Price Forecast; forecast models; forecast techniques (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-348-1_26

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DOI: 10.2991/978-94-6463-348-1_26

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