Türkiye'de Konut Fiyatları Dinamiklerinin Dalgalanma Etkisi Hipotezi Çerçevesinde Analizi Özet

Çalışmada Türkiye’deki 26 bölge düzeyi için bölgesel konut fiyatlarında “dalga- lanma etkisi” hipotezinin geçerliliği Merkez Bankası Veri Dağıtım Sistemi’nden elde edilen aylık (2010Ocak1-2014Ocak1), üçer aylık (2010Q1-2014Q1) ve yıl- lık frekanstaki (2010-2014) konut fiyat endeksi veri setleri için incelenmektedir. İlk kez, İngiliz konut ekspertizleri tarafından İngiltere’nin güney doğusunda mey- dana gelen şokların zamanla İngiltere’nin kuzey batısındaki konut fiyatlarını etki- lemesi olarak gözlemlenen bu etkinin varlığı Türkiye’de aylık konut fiyat endek- si veri seti için panel SURADF birim kök sınaması; üçer aylık veri seti için panel CADF birim kök sınaması ve yıllık veri seti için birinci nesil panel birim kök test- leri ile incelenmiş ve durağan olan serilerin ortalamaya dönüş süreleri yarı-ömür analizi ile hesaplanmıştır. Durağanlık analizi sonuçlarına göre, aylık veri seti için TR21,TR71,TR72 ve TRC3 bölgelerinde ve üçer aylık veri seti için sadece TR71 bölgesinde dalgalanma etkisi hipotezinin geçerli olduğu; ancak, yıllık veri seti için hiçbir bölge düzeyinde dalgalanma etkisi hipotezinin geçerli olmadığı sonucuna ulaşılmıştır.

The Analysis of Turkish House Price Dynamics in the Framework of Ripple Effect

The study focuses on the validity of “Ripple Effect” hypothesis on regional ho- using prices in 26 regions in Turkey, using monthly (2010Jan-2014Jan), quar- terly (2010Q1-2014Q1) and annual (2010-2014) House Price Index data obtai- ned from Central Bank Data Distribution System. First, it was British housing ex- perts who have observed the existence of this effect described as shocks oc- curred in South East England affecting housing prices in North West of England over time. Panel SURADF Unit Root Test for monthly data; Panel CADF Unit Root Test for quarterly data and First Generation Panel Unit Root Test for annual data are used to analyze the validity of this effect in Turkey. Also, mean reversi- on is calculated by half-life analysis. According to the results of stationarity analy- sis, Ripple Effect Hypothesis is valid for monthly data in TR21, TR71, TR72 and TRC3 region levels and for quarterly data in only TR71 region level, but any re- gional level Ripple Effect occurs for annual data.

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