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A Peer-reviewed scientific articles/A1 Journal article (refereed), original research
      
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Forecasting Quarterly Russian GDP Growth with Mixed-Frequency Data, Russian Journal of Money and Finance 1 (2019). Mikosch, Heiner; Solanko, Laura


Category A Peer-reviewed scientific articles
Sub-category A1 Journal article (refereed), original research
auki Internal authors
All authors as text Mikosch, Heiner; Solanko, Laura 
Number of authors
Status Published
Year of publication 2019 
Date 15.03.2019 
Name of article Forecasting Quarterly Russian GDP Growth with Mixed-Frequency Data 
Name of journal Russian Journal of Money and Finance
Volume of issue 78 
Number of issue
Pages 19-35 
Abstract This paper presents a pseudo real‐time out‐of‐sample forecast exercise for short‐term forecasting and nowcasting quarterly Russian GDP growth with mixed‐frequency data. We employ a large set of indicators and study their predictive power for different subperiods within the forecast evaluation period 2008–2016. Four indicators consistently figure in the list of top-performing indicators: the Rosstat key sector economic output index, the OECD composite leading indicator for Russia, household banking deposits, and money supply M2. Aside from these indicators, the top indicators in the 2008–2011 evaluation period are traditional real‐sector variables, while those in the 2012–2016 evaluation period largely comprise monetary, banking sector and financial market variables. We also compare the forecast accuracy of three different mixed‐frequency forecasting model classes (bridge equations, MIDAS models, and U-MIDAS models). Differences between the performance of model classes are generally small, but for the 2008–2011 period MIDAS models and U-MIDAS models outperform bridge equation models.
Free text descriptor in Finnish ennusteet; bruttokansantuote; indikaattorit; Venäjä 
Free text descriptor in English forecasting, Russia, GDP growth, mixed frequency data, MIDAS, bridge equations 
JEL-codes C53, E27 
ISSN / e-ISSN 2618-6799 
auki Internet addresses