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Forecasting Russian GDP, Inflation, Interest Rate, and Exchange Rate Using DSGE-VAR Model

Author

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  • Artur Sharafutdinov

    (Bank of Russia; RANEPA)

Abstract

This paper compares, on Russian quarterly data for 2003–2021, the forecast performance of a small-scale dynamic stochastic general equilibrium model (DSGE model) and the DSGE-VAR model as a Bayesian vector autoregression (VAR) which uses priors from this DSGE model. The forecast performance of the DSGE-VAR model turns out to be higher than that of the DSGE model for output growth and inflation over the one-year horizon and for the interest rate and exchange rate over a two-year horizon. Meanwhile, the DSGE-VAR model, on average, predicts GDP, inflation, and the exchange rate better and the interest rate worse than the first-order autoregressive model that serves as a benchmark.

Suggested Citation

  • Artur Sharafutdinov, 2023. "Forecasting Russian GDP, Inflation, Interest Rate, and Exchange Rate Using DSGE-VAR Model," Russian Journal of Money and Finance, Bank of Russia, vol. 82(3), pages 62-86, September.
    • Handle: RePEc:bkr:journl:v:82:y:2023:i:3:p:62-86
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    References listed on IDEAS

    as
    1. Peter N. Ireland, 2007. "Changes in the Federal Reserve's Inflation Target: Causes and Consequences," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(8), pages 1851-1882, December.
    2. Демешев Борис Борисович & Малаховская Оксана Анатольевна, 2016. "Макроэкономическое Прогнозирование С Помощью Bvar Литтермана," Higher School of Economics Economic Journal Экономический журнал Высшей школы экономики, CyberLeninka;Федеральное государственное автономное образовательное учреждение высшего образования «Национальный исследовательский университет «Высшая школа экономики», vol. 20(4), pages 691-710.
    3. Del Negro, Marco & Schorfheide, Frank & Smets, Frank & Wouters, Rafael, 2007. "On the Fit of New Keynesian Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 123-143, April.
    4. Marco Del Negro & Frank Schorfheide, 2004. "Priors from General Equilibrium Models for VARS," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(2), pages 643-673, May.
    5. Sergey Slobodyan & Raf Wouters, 2012. "Learning in a Medium-Scale DSGE Model with Expectations Based on Small Forecasting Models," American Economic Journal: Macroeconomics, American Economic Association, vol. 4(2), pages 65-101, April.
    6. Marco Del Negro & Frank Schorfheide, 2003. "Take your model bowling: forecasting with general equilibrium models," Economic Review, Federal Reserve Bank of Atlanta, vol. 88(Q4), pages 35-50.
    7. Raffaella Giacomini, 2013. "The relationship between DSGE and VAR models," CeMMAP working papers CWP21/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Raffaella Giacomini, 2013. "The relationship between DSGE and VAR models," CeMMAP working papers 21/13, Institute for Fiscal Studies.
    9. Dmitry Kreptsev & Sergei Seleznev, 2018. "Forecasting for the Russian Economy Using Small-Scale DSGE Models," Russian Journal of Money and Finance, Bank of Russia, vol. 77(2), pages 51-67, June.
    10. Pop, Raluca-Elena, 2017. "A small-scale DSGE-VAR model for the Romanian economy," Economic Modelling, Elsevier, vol. 67(C), pages 1-9.
    11. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    12. Raffaella Giacomini, 2013. "The Relationship Between DSGE and VAR Models," Advances in Econometrics, in: VAR Models in Macroeconomics – New Developments and Applications: Essays in Honor of Christopher A. Sims, volume 32, pages 1-25, Emerald Group Publishing Limited.
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    More about this item

    Keywords

    forecasting; DSGE-VAR; DSGE; BVAR; Russian economy;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation: Models and Applications

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