LEE- Gayrimenkul Geliştirme-Yüksek Lisans
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ÖgeInvestigation of the effect of CDS premiums on housing prices in Türkiye(Graduate School, 2023-06-16)Studies in the literature show a decrease in lending by financial institutions and banks in countries due to increased financing costs associated with increases in CDS premiums. As a result, a noticeable decrease in housing prices is observed (Benbouzid, Mallick, & Pilbeam, 2018). In this context, this thesis examines how the Türkiye CDS premium affects housing prices and how an increase in CDS premiums affects housing prices. Additionally, this thesis will statistically analyze other macroeconomic variables that affect housing prices and the interrelationships among these variables. Studies on the relationship between CDS premiums and housing prices have shed light on how changes in CDS premiums can affect credit availability for homebuyers and overall housing demand, providing insights into potential mechanisms through which CDS premiums can impact housing prices. These studies emphasize the importance of considering other factors, such as economic conditions and other market factors, that can influence this relationship. Previous research on the determinants of Türkiye's CDS premiums has shown that volatility in premiums is more influenced by global than domestic variables. However, the high volatility in premiums is believed to stem from political and economic issues. This thesis aims to investigate the relationship between CDS premiums and Turkish housing prices, as well as other macroeconomic variables that influence this relationship. A vector autoregression (VAR) model has been used to statistically analyze variables such as the housing price index, effective exchange rate, BIST 100 (stock market index), inflation, interest rates, and Türkiye's CDS premiums. Econometric approaches such as VAR, impulse-response analysis, and Granger causality tests have been employed to determine the causal relationship among the variables. The analysis covers the period from September 2010 to December 2022, and the variables have been examined on a monthly basis. The data used in this thesis have been obtained from reliable sources such as the Central Bank, and Bloomberg. The selected timeframe of 2010-2022 has provided a comprehensive understanding of the relationship between Türkiye's CDS premiums, selected macroeconomic variables, and housing prices. The thesis hypothesises that increasing CDS premiums will lead to decreasing housing prices in Türkiye. Based on the findings of previous studies and the literature review, CDS premiums are known to be influenced by various variables such as interest rates, exchange rates, inflation, and the stock market. The results of the multivariate VAR model reveal that changes in Türkiye's 5-year CDS premiums have a positive impact on housing prices in the medium term. Furthermore, the model yields results indicating the role of other macroeconomic variables in the relationship between CDS premiums and housing prices. In the VAR technique, the time series of the variables involved in the analysis must be stationary and does not have unit roots. Therefore, the analysis includes the variables by taking their logarithms. Subsequently, the Augmented Dickey-Fuller (ADF) unit root test has been applied to the series, and it has been observed that the series are not stationary. Taking first differences has been applied to make the logarithmic series stationary. However, when the housing price index variable is differenced once in the ADF test, it is still not stationary. Therefore, a Perron unit root test that takes into account structural breaks has been applied to this variable, and it has been observed that it is stationary after the first difference. After determining the optimum lag length based on information criteria in the VAR analysis, the second lag length with the minimum values of all criteria has been selected. After determining the optimum lag length, the VAR model has been constructed. After constructing the VAR model, the analysis proceeds to variance decomposition. The results of variance decomposition show that in the first period, the variance of the housing price index variable changes solely due to its own shocks and does not receive any contribution from other variables. Starting from the second period, it is observed that the variance of the housing price index variable is explained to varying degrees by other variables. In the second period, it is seen that 92.88% of the volatility in the housing price index is caused by its own shocks, 3.60% by the real effective exchange rate, and 2.97% by other variables such as inflation. According to the results of variance decomposition, the effects of the real effective exchange rate and inflation on the variance of the housing price index variable increase over ten periods. This indicates that over time, these variables become more important in explaining the movements of the housing price index variable. After ten periods, the most critical variables that cause changes in the housing price index are inflation (10.7%) and the real effective exchange rate (8.7%). Overall, the variance decomposition analysis demonstrates that the fluctuations in the housing price index variable are caused by both its own shocks and shocks from other variables, especially inflation and the real effective exchange rate. According to the variance decomposition results for the variable of Türkiye's 5-year CDS premiums, in the first period, 99.8% of the variance is solely due to its own shocks. According to the results of variance decomposition analysis, the impact of Türkiye's 5-year CDS premiums on the variance of the housing price index variable has been minimal over ten periods, explaining only 0.2% of the total variance. These results indicate that inflation (10.7%) is the most significant explanatory variable for housing prices and CDS premiums. The findings of this thesis contribute to our understanding of factors influencing housing prices, particularly in developing economies like Türkiye. The study emphasizes the importance of considering CDS premiums and macroeconomic variables when analyzing the housing market. Overall, this thesis contributes to our understanding of the driving forces behind increasing housing costs in developing economies and provides insights for policymakers in Türkiye regarding housing policy.
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ÖgeSeasonality of short-term rentals case study from AIRBNB in İstanbul(Graduate School, 2022)The short-term rental market has multiplied over the last decade. Airbnb (and other online accommodation sharing platforms, which provide an online market that links people with each other as host and guest system) is attracting much interest, as it has implications for the real estate market worldwide. The impacts vary across the globe depending on the context. As Airbnb comes at the forefront of short-term rental platforms in this market in Istanbul, Turkey, with the biggest share, attracting many researchers trying to answer the generated and raised questions. The Airbnb platform is connected to several markets like the sharing economy, hospitality, and housing. the researchers in every branch trying to study the effects of Airbnb in each market. However, the literature is still limited but for the past four years, it witnessed development as Airbnb grew and expanded its platforms to include the hotels as well. Airbnb is well- known it started working in Istanbul in 2010 according to Yuksel (2019) and most resources. However, the dataset recorded one review in June 2009 in the Uskudar district in the Anatolian side of Istanbul. Nevertheless, Airbnb flourished and expanded more in 2010, also more reviews were recorded starting from March 2010. Since then, the number of listings is rising reaching 24,519 listings and over 194,000 reviews have been written by guests in the most recent collected dataset (February 2021).