Modeling Azerbaijan’s Inflation and Output Using a Factor-Augmented Vector Autoregressive (FAVAR) Model

Vugar Rahimov (), Nijat Guliyev () and Vugar Ahmadov
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Vugar Rahimov: Central Bank of Azerbaijan Republic
Nijat Guliyev: Central Bank of Azerbaijan Republic
Vugar Ahmadov: Central Bank of Azerbaijan Republic

No 1903, Working Papers from Central Bank of Azerbaijan Republic

Abstract: In this study, we build and use a factor-augmented vector autoregressive (FAVAR) model to forecast inflation and output in Azerbaijan. The FAVAR model is particularly effective in data-rich environments, alleviating the curse of dimensionality of the standard VAR model and handling omitted variable bias. Using 77 variables for factor extraction and quarterly data for the period 2003 to 2018, we build several multivariate models, including a FAVAR model, and compare their performance with that of a benchmark univariate model. Our findings show that almost all of the multivariate models underperform in comparison with the univariate model. This result is in line with the literature, which finds that simple models are better forecasters of some macroeconomic variables, especially inflation. We acknowledge that the results might be affected by the relatively short length of the sample period and existence of irregularities in the data.

Keywords: Ä°nflation; output; principal components; forecasting ability; FAVAR; Azerbaijan (search for similar items in EconPapers)
JEL-codes: C53 E17 E3 E31 E37 (search for similar items in EconPapers)
Pages: 37 pages
Date: 2019-06-06
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Persistent link: https://EconPapers.repec.org/RePEc:aze:wpaper:1903

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