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FAVAR (Factor-Augmented Vector Autoregression) Modeli Literatür Taraması

Favar (Factor-Augmented Vector Autoregressıon) Model Literature Review

Journal Name:

  • Fiscaoeconomia

Publication Year:

  • 2017

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Keywords (Original Language):

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Abstract (2. Language): 
In the Vector Autoregressive (VAR) models, which are widely used in economic studies and developed by Sims (1980), impulse response functions can only be obtained from variables included only because of the infrequent use of information sets, and the dimensions of structural shocks can not be measured precisely. It is also not possible that for some variables to be represented by a single time series. The VAR estimation is insufficient for parsing operations involving large data sets. FAVAR (Factor Augmented Vector Autoregression) method was developed by Bernanke, Boivin and Eliasz (2005) and this method can use large data sets. In this study, FAVAR method is tried to be explained by comparing with VAR, and a literature search is being conducted in this subject.
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Abstract (Original Language): 
Ekonomik çalışmalarda yaygın biçimde kullanılan ve Sims (1980)’in literatüre kazandırdığı Vektör Otoregresyon (VAR) modellerinde, tüm bilgi setlerinin bir kısmının kullanımı nedeniyle, sadece dahil edilen değişkenler için etki tepki fonksiyonları elde edilebilir ve yapısal şokların boyutları tam olarak ölçülemez. Ayrıca bazı değişkenlerin tek bir zaman serisi ile temsil edilmeleri mümkün değildir. Bernanke, Boivin ve Eliasz (2005)’ın geliştirdiği FAVAR (Faktör Arttırımlı Vektör Otoregresyon) yöntemi büyük veri setlerini kullanabilmeye imkan tanımaktadır. Böylece FAVAR yöntemi büyük veri setlerinde etken olan makroekonomik faktörleri sistematik ve tutarlı biçimde tahmin edebilmektedir. Bu çalışmada FAVAR yöntemi VAR ile kıyaslanarak açıklanmış ve bu konuda bir literatür taraması yapılmıştır.
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REFERENCES

References: 

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