Geçinme Endeksi Değerinin Araştırılması ve Tahminlenmesi: Türkiye Geneli ve İstanbul Özeli Örneği

Öz

Geçinme endeksi, hane halklarının mevcut yaşam standartlarını sürdürebilmeleri için gereken harcama düzeyini gösteren ve toplumun alım gücünü doğrudan yansıtan temel bir ekonomik göstergedir. Bu endeksteki değişimlerin izlenmesi, hem uygulanan ekonomi politikalarının etkinliğini ölçmek hem de toplumsal refahın korunmasına yönelik stratejiler geliştirmek açısından kritik bir önem taşımaktadır. Bu çalışmada, Türkiye geneli ve İstanbul özelindeki geçinme endeksi değerlerini analiz etmek amacıyla kapsamlı bir veri setinden yararlanılmıştır. Araştırmanın veri seti, Türkiye Cumhuriyet Merkez Bankası (TCMB) ve Türkiye İstatistik Kurumu (TÜİK) verilerinden derlenen Ağustos 2013 ile Aralık 2025 dönemine ait 149 aylık süreci kapsamaktadır. Analizlerde algoritma olarak, tahmin başarısını belirlemek amacıyla Bagging topluluk öğrenmesi ile Değişken Model Ağacı (AMT) algoritmasının hibrit bir yapısı kullanılmaktadır. Ayrıca, endeks üzerinde etkili olan değişkenleri belirlemek için ReliefF öznitelik seçimi algoritmasından yararlanılmaktadır. Elde edilen sonuçlar, algoritmanın hem ulusal hem de bölgesel ölçekte yüksek bir tahmin başarısı sergilediğini göstermektedir. Özellikle 2026 yılına yönelik yapılan 12 aylık tahminlerde, geçinme endeksinin her iki bölgede de paralel ancak İstanbul’da daha keskin bir artış eğilimi içerisinde olduğu görülmektedir. Değişkenlerin önem sıralamasına bakıldığında ise konut harcamalarının hem Türkiye genelinde hem de İstanbul’da geçinme maliyetlerini tetikleyen en temel unsur olduğu belirlenmektedir. İstanbul özelinde ulaştırma maliyetlerinin Türkiye geneline kıyasla daha baskın bir ağırlığa sahip olması, bölgesel dinamiklerin farklılaştığını ortaya koymaktadır.

Anahtar Kelimeler

• Geçinme endeksi
• bagging
• değişken model ağacı
• reliefF
• tahminleme.

Destekleyen Kurum

Çalışmada herhangi bir kurum ya da kuruluştan destek alınmamıştır.

Etik Beyan

Etik kurul belgesi gerektiren bir çalışma değildir.

Teşekkür

Çalışmada herhangi bir kurum ya da kuruluştan destek alınmamıştır.

Investigation and Forecasting of The Cost of Living Index: The Case of Türkiye and İstanbul

Öz

The cost-of-living index represents the spending level required for households to maintain their current living standards. It directly reflects the purchasing power of society. Monitoring changes in this index is critical for measuring the effectiveness of economic policies. It also helps develop strategies to protect social welfare. This study uses a comprehensive dataset to analyze cost of living index values for Türkiye and Istanbul. The dataset covers 149 months between August 2013 and December 2025. These data come from the Central Bank of the Republic of Türkiye (CBRT) and the Turkish Statistical Institute (TURKSTAT). The analysis employs a hybrid structure of Bagging ensemble learning and the Alternating Model Tree (AMT) algorithm. This approach determines the forecasting success. Additionally, the ReliefF feature selection algorithm identifies the effective variables the index. Results show high forecasting success at both national and regional levels. The 12-month forecasts for 2026 indicate a parallel upward trend in both regions. However, Istanbul shows a sharper increase. Housing expenses emerge as the primary factor driving living costs in both Türkiye and Istanbul. Transportation costs hold more weight in Istanbul compared to the national average. This difference highlights varying regional dynamics.

Anahtar Kelimeler

• The cost-of-living index
• bagging
• alternating model tree
• reliefF
• forecasting

Destekleyen Kurum

No support is taken from any institution or organization.

Etik Beyan

The study does not necessitate an approval of ethical committee.

Teşekkür

No support is taken from any institution or organization.

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