..., the ARIMAX model integrates time series analysis and external factors to enhance modelling and forecasting accuracy. Findings The investigation reveals that MLR and RR yield accurate predictions by considering a range of influential variables. The hybrid ARIMAX model further enhances predictive...

...Xingrui Zhang; Eunhwa Yang; Yunpeng Wang Purpose Private residential construction spending (PRRESCON) is an important indicator for assessing housing supply/demand and economic strength. Currently, there are no comprehensive studies on PRRESCON forecasting. This study aims to address the gap...

..., the Granger causality test was used first to identify causal relationships between HVI and BP. Subsequently, the vector autoregression model was implemented in an attempt to observe impulse–response relationships and to create a forecast for HVI. Findings Bidirectional causal relationships were observed...

...Vinayaka Gude Purpose This research developed a model to understand and predict housing market dynamics and evaluate the significance of house permits data in the model’s forecasting capability. Design/methodology/approach The research uses a multilevel algorithm consisting of a machine...

...Xin Janet Ge; Vince Mangioni; Song Shi; Shanaka Herath Purpose This paper aims to develop a house price forecasting model to investigate the impact of neighbourhood effect on property value. Design/methodology/approach Multi-level modelling (MLM) method is used to develop the house price...

... policy uncertainty House prices volatility G7 countries GARCH-MIDAS model Forecasting Developed economies In today’s era, numerous challenges have occurred, resulting in global economic and political uncertainties. These uncertainties start with “Arab Spring,” after which several events have...

... 08 2021 © Emerald Publishing Limited 2021 Emerald Publishing Limited Licensed re-use rights only House prices Housing market analysis G7 countries Volatility Forecasting MF-DFA technique In today’s world, the housing sector is considered one of the assets that serve...

... is to compare different models’ performance in modelling and forecasting the Finnish house price returns and volatility. Having noted the importance of the housing market, house price analysis of individual markets has been the subject of an increasing amount of studies. However, the focus has been...

...Behrooz Nazemi; Mohsen Rafiean 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...

... of this study is to detect homogeneous housing market areas among 196 districts of 5 major cities of Turkey in terms of house sale price indices. The second purpose is to forecast these 196 house sale price indices. In this paper, the authors use the monthly house sale price indices of 196 districts of 5...

... housing market. One of the main objectives is to find a model based on internet search interest that generates reliable real-time forecasts. Design/methodology/approach – Starting from seven individual real-estate-related Google search volume indices, a multivariate probit model is derived...

...Ali Hepşen; Metin Vatansever Purpose It is important to forecast index series to identify future rises, falls, and turning points in the property market. From the point of this necessity and importance, the main purpose of this paper is to forecast the future trends in Dubai housing market...

... (CBI)”. One‐way fixed effects and one‐way random effects approaches (which are panel data approaches) are applied to model housing price forecasting function in Tehran's 20 different zones. Results are compared with ordinary least squares approach which is a common approach in this field. Finally...