Time Series Analysis for Detecting Real Estate Bubbles A Case Study of East Marmara
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Keywords:
Time Series Analysis, Bubble Detection, Real Estate, Augmented Dickey-Fuller, GSADFAbstract
A bubble occurs when the value of assets significantly exceeds their intrinsic worth. Detecting
bubbles is crucial for policymakers and regulators to mitigate financial crises. This study utilizes a time
series analysis approach to detect real estate bubbles in the East Marmara region, encompassing Kocaeli,
Sakarya, Bolu, Düzce and Yalova. Residential Property Price Index (RPPI) dataset (2017=100), covering
the duration from January 2013 to January 2024, was acquired from the Central Bank of the Republic of
Turkey's Electronic Data Distribution System (TCMB-EVDS). Using the Augmented Dickey-Fuller
(ADF), Supremum ADF (SADF), Generalized SADF (GSADF), and Rolling ADF (RADF) tests. The
SADF test returned a t-statistic of 32.80130 (p < 0.0001), indicating strong evidence of bubble-like
behavior, while the GSADF test confirms the occurrence of multiple speculative bubbles with similar
statistical significance. The RADF test provided insights into real-time bubble progression, detecting a
peak in speculative activity in 2022 when the ADF statistic (5.743343, p < 0.0001) crossed critical
thresholds. Across all tests, the results indicate that real estate prices in the East Marmara region showed
an explosive growth during 2021 and 2022 years, followed by a correction phase at the end of 2022.
These patterns coincide with a steep increase in the Residential Property Price Index (RPPI), highlighting
the political and economic influences in the region in recent years. These results offer valuable insights
for policymakers and market participants in detecting and managing speculative behavior in real estate
markets and making changes to minimize financial instability.
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