ANALYZING THE IMPACT OF THE 2023 GENERAL ELECTIONS ON LAND PRICES USING MACHINE LEARNING: A CASE STUDY IN ÇANAKKALE, TURKEY

Year 2025, Volume: 13 Issue: 1, 147 - 164, 01.03.2025

Simge Doğan , Levent Genç , Sait Can Yücebaş , Şükran Yalpır

https://doi.org/10.36306/konjes.1579931

Abstract

This study analyses the impact of the general elections to be held on 14 May 2023 on the real estate market in Turkey. The aim of the study is to develop a model to predict land unit prices (₺/m²) by analysing land prices, exchange rates and gold values observed before (February-March-April) and after (May-June-July) elections for Ayvacık, Bayramiç, Biga, Çan, Eceabat, Ezine, Gelibolu, Lapseki, Merkez and Yenice districts of Çanakkale province. Daily fluctuations in foreign exchange and gold values, which are the main economic parameters in the study, were recorded during the election period. The findings of this research, which predicts price movements in the property market using machine learning methods such as regression trees, reveal that unit prices of land generally tend to increase with increases in exchange rates, but in some districts where gold prices increase, the unit price shows a reverse trend. This is attributed to the fact that investors prefer gold as a safer asset in times of economic uncertainty. The results obtained can help investors and buyers to predict future trends in property prices, as well as contribute to the development of economic policies by experts to stabilise fluctuations in investment instruments.

Keywords

Election, Sustainabilty Land Price, Economic Parameters, Regression Tree, Machine Learning

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