BOFIT Discussion Papers, Institute for Economies in Transition, Bank of Finland
No 19/2015:
Nowcasting and short-term forecasting of Russian GDP with a dynamic factor model
Alexey Porshakov ()
, Elena Deryugina ()
, Alexey Ponomarenko ()
and Andrey Sinyakov ()
Abstract: Real-time assessment of quarterly GDP growth rates is
crucial for evaluation of economy’s current perspectives given the fact
that respective data is normally subject to substantial publication delays
by national statistical agencies. Large information sets of real-time
indicators which could be used to approximate GDP growth rates in the
quarter of interest are in practice characterized by unbalanced data, mixed
frequencies, systematic data revisions, as well as a more general curse of
dimensionality problem. The latter issues could, however, be practically
resolved by means of dynamic factor modeling that has recently been
recognized as a helpful tool to evaluate current economic conditions by
means of higher frequency indicators. Our major results show that the
performance of dynamic factor models in predicting Russian GDP dynamics
appears to be superior as compared to other common alternative
specifications. At the same time, we empirically show that the arrival of
new data seems to consistently improve DFM’s predictive accuracy throughout
sequential nowcast vintages. We also introduce the analysis of nowcast
evolution resulting from the gradual expansion of the dataset of
explanatory variables, as well as the framework for estimating
contributions of different blocks of predictors into now-casts of Russian
GDP.
Keywords: GDP nowcast; dynamic factor models; principal components; Kalman filter; nowcast evolution; (follow links to similar papers)
JEL-Codes: C53; C82; E17; (follow links to similar papers)
41 pages, May 28, 2015
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