Description
Title: Evidence from Turkey for the DMA Method for Predicting House Prices
Abstract: This study’s objectives are to examine the dynamics of Turkey’s housing market and the effects of various factors on housing prices. Turkey, one of the developing nations with a booming housing market, attracts many foreign real estate investors and offers lucrative real estate investments. The dynamic model averaging (DMA) methodology is used in this study to forecast monthly house price growth. Google online searches are included in the study due to the rising use of information technologies. Twelve independent variables were used between January 2010 and December 2019 for this purpose, with the Residential Property Price Index serving as the dependent variable. The analysis’ findings revealed that some factors, including bond yields, the amount of mortgages outstanding, foreign direct investments, unemployment, industrial production, exchange rates, and the Google Trends index, influence the residential property price index.
Keywords: housing price prediction; RPPI; DMA; Google Trends index; Turkey
Paper Quality: SCOPUS / Web of Science Level Research Paper
Subject: Economics
Writer Experience: 20+ Years
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