House price modelling under covid-19 analysis of parameters on online listing platforms

dc.contributor.advisor Arslanlı, Kerem Yavuz
dc.contributor.author Dibek, Samet
dc.contributor.authorID 516201014
dc.contributor.department Real Estate
dc.date.accessioned 2024-08-21T08:11:46Z
dc.date.available 2024-08-21T08:11:46Z
dc.date.issued 2023-01-05
dc.description Thesis (M.Sc.) -- İstanbul Technical University, Graduate School, 2023
dc.description.abstract This study examined how Covid-19 affected house prices in online listing platforms for the Istanbul Metropolitan area. In all online listing platforms in Turkey, net living area, building age, being in a gated community, the number of floors and floor level of the apartment is the primary filtering and evaluation criteria. We analyzed how and in what direction these parameters affect house prices, depending on people's preferences, from the beginning of 2020, which is considered the beginning of Covid-19, to June of 2021, the period when the life began to continue relatively independent from covid-19. While doing this, we had 635,234 observations of house sales from online listings. We divided the data into three groups for houses with lower, middle and upper-income level prices, running them in a split model would be a better option when considering Istanbul's metropolitan structure. For each dataset, we have created regression models on a monthly basis and tracked the change of parameter coefficients. While all parameters in the model gave meaningful results for the lowest price segment, the significance level decreased as the prices increased. During the pandemic, the low-income group's tendency has evolved towards a modern form of housing in gated communities. As a result, the tendency to live in old buildings has decreased and the "large space requirement" related to size has left its place for "more room" houses in these preferences. When we run two co-models constructed at the beginning and end of the period (June of 2020 and 2021), the coefficients for living in the gated communities increased by 14%, the coefficients for the number of rooms increased by 7% and the coefficients for the net living area decreased by 26%. The building age coefficient changed its sign to negative as expected. Furthermore, none of the parameters except the net living area in the highest price group yielded to a significant result.
dc.description.degree M.Sc.
dc.identifier.uri http://hdl.handle.net/11527/25190
dc.language.iso en_US
dc.publisher Graduate School
dc.sdg.type Goal 11: Sustainable Cities and Communities
dc.subject urban housing
dc.subject kentsel konut
dc.subject machine learning
dc.subject makine öğrenmesi
dc.subject Multiple linear regression
dc.subject Çoklu doğrusal regresyon
dc.title House price modelling under covid-19 analysis of parameters on online listing platforms
dc.title.alternative Covid-19 pandemi döneminde online emlak platformlarındaki parametreler kullanılarak konut fiyatlarının modellenmesi
dc.type Master Thesis
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