Aykut EKİCİ HTTPS ORCİD.ORG, Burçhan SAKARYA

Özel Tüketim Talebinin Yüksek Frekans ve Şimdi Tahmin ile Modellenmesi

GSYH’nın en büyük bileşeni olan özel tüketimin tahmin edilmesi, diğer makro ve finansal büyüklüklerle olan güçlü ilişkisi nedeniyle oldukça önemlidir. Çalışma, özel tüketim harcamaları için MIDAS modeli ile yüksek frekanslı değişkenlerin modele eklenmesinin tahmin kabiliyetine etkisini incelemektedir. Bu amaçla, 2011 birinci çeyreği ile 2019 üçüncü çeyreği arasındaki dönem için çeyreklik, aylık, haftalık ve günlük frekansa sahip değişkenler üzerinden tahmin modelleri üretilmiş ve tüm dönem için tahmin performansları karşılaştırılmıştır. Çalışmadan elde edilen temel sonuçlar şunlardır; yüksek frekanslı değişkenlerin kullanılması tahmin performansını artırmaktadır ve finansal bilgi taşıyan kredi, faiz ile borsa göstergeleri tüketimi tahmin etmede iyi bir yüksek frekanslı değişken konumundadırlar.

Modelling Private Domestic Consumption with High Frequency Data and Nowcasting

Forecasting private consumption expenditures is particularly important for analysing economic and financial activity, as this demand component is closely related with many macroeconomic and financial variables. This study provides a forecast framework utilizing high frequency data within MIDAS methodology. To this end a sample period of 2011Q1 - 2019:Q3 has been tested, incorporating quarterly, monthly, weekly and even daily data to the proposed estimation models. Furthermore, comparative performance of the models is discussed. The main findings of the study are; use of higher frequency data improves forecast performance significantly, and incorporating variables, which carry financial market information such as loans, interest rates and equity prices enhances estimation and forecast performance.

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