Predicting House Prices Using DMA Method: Evidence from Turkey

Nuri Hacıevliyagil,Krzysztof Drachal,Ibrahim Halil Eksi

doi:10.3390/economies10030064

Nuri Hacıevliyagil, Krzysztof Drachal + Show 1 more

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https://doi.org/10.3390/economies10030064

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Abstract

The aim of this study is to analyze the dynamics of the housing market in Turkey’s economy and to examine the impact of variables related to housing prices. Preferred by many international housing investors, Turkey hosts profitable real estate investments as one of the developing countries with a shining housing market. This study applies the dynamic model averaging (DMA) methodology to predict monthly house price growth. With the increasing use of information technologies, Google online searches are incorporated into the study. For this purpose, twelve independent variables, with the Residential Property Price Index as the dependent variable, were used in the period January 2010–December 2019. According to the analysis results, it was observed that some variables, such as bond yields, the level of mortgages, foreign direct investments, unemployment, industrial production, exchange rates, and Google Trends index, are determinants of the Residential Property Price Index.

Highlights

Using dynamic model averaging (DMA) Method: Evidence fromHousing, an important subbranch of the real estate market, is an important part of the sustainable economy
The prelimary simulations based on the first three-fourths of observations indicated that out of the considered grid of forgetting factors, the mean absolute scaled error (MASE) measure is minimized for the following combination: α = 0.97 and λ = 0.90
It can be seen that the DMA-based model combination schemes generally produced less accurate forecasts than those from the ARIMA models

Summary

Introduction

Using DMA Method: Evidence fromHousing, an important subbranch of the real estate market, is an important part of the sustainable economy. The housing market attracts investors, who perceive real estate as a consumption good, and as an asset in which money can be allocated (Gebeşoğlu 2019). In the real estate sector, which has become a very profitable investment tool, especially in the last 15 years , housing prices determine the profitability of the sector At this point, the determination of housing prices has been one of the most important subtopics of the sector. The determination of housing prices has been one of the most important subtopics of the sector This topic has prompted many market players, from residential investors to real estate investment trusts and from individual investors to government officials, to predict the movement of housing prices, and they use a variety of methods for this (Gupta et al 2011; Ghysels et al 2013; Yemelina et al 2018; Kishor and Marfatia 2018)

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