Forecasting Russian Macroeconomic Indicators with BVAR

Boris Demeshev and Oxana Malakhovskaya

HSE Working papers from National Research University Higher School of Economics

Abstract: This paper evaluates the forecast performance of Bayesian vector autoregressions (BVARs) on Russian data. We estimate BVARs of different sizes and compare the accuracy of their out-ofsample forecasts with those obtained with unrestricted vector autoregressions and random walk with drift. We show that many Russian macroeconomic indicators can be forecast by BVARs more accurately than by competing models. However, contrary to several other studies, we do not confirm that the relative forecast error monotonically decreases with increasing the crosssectional dimension of the sample. In half of those cases where a BVAR appears to be the most accurate model, a small-dimensional BVAR outperforms its high-dimensional counterpart.

Keywords: VAR; BVAR; forecasting; Bayesian estimation (search for similar items in EconPapers)
JEL-codes: C11 C13 C53 (search for similar items in EconPapers)
Pages: 17 pages
Date: 2015
New Economics Papers: this item is included in nep-cis, nep-for, nep-mac, nep-ore and nep-tra
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Published in WP BRP Series: Economics / EC, October 2015, pages 1-17

Downloads: (external link)
http://www.hse.ru/data/2015/11/10/1078468762/105EC2015.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hig:wpaper:105/ec/2015

Access Statistics for this paper

More papers in HSE Working papers from National Research University Higher School of Economics
Bibliographic data for series maintained by Shamil Abdulaev () and Shamil Abdulaev ().