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Research paper thumbnail of Forecasting Russian Macroeconomic Indicators with BVAR

RePEc: Research Papers in Economics, 2015

This paper evaluates the forecast performance of Bayesian vector autoregressions (BVARs) on Russi... more 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.

Research paper thumbnail of Macroeconomic Forecasting with a Litterman's BVAR Model

This paper compares the forecasting performance of random walk, frequentist vector autoregression... more This paper compares the forecasting performance of random walk, frequentist vector autoregression (VAR), and Bayesian vector autoregression with Minnesota prior (BVAR) models on quarterly Russian data sample running from 1995 to 2014. Maximal number of variables included in the model is equal to 14 that requires an endogenous search of optimal shrinkage hyperparameter. The search procedure follows [Banbura et al., 2010; Bloor, Matheson, 2011].According to the selection method the shrinkage hyperparameter equates the forecasting quality of the frequentist VAR and BVAR for the minimal considered dimension of the model (three variables). For any dimension of the BVAR model the optimal shrinkage hyperparameter is robust to considered functions of relative forecasting accuracy.We show that the BVAR provides a more accurate forecast than the frequentist VAR on the studied sample. For key macro indicators (the industrial production index, consumer priceindex and the interbank interest rate), forecasting horizons, and all model sizes, the mean squared error of the BVAR is lower than that of the frequentist VAR. Moreover, the results show that the forecast made using the BVAR is more precise than the forecast made using random walk model for the CPI and using white noise model for the interbank rate. However, the BVAR cannot beat the random walk while forecasting the industrial production index.

Research paper thumbnail of Essays on forecasting and modelling an energy-based economy

Il y a un consensus que la sévérité des chocs sur les marchés pétroliers tend à diminuer, ainsi q... more Il y a un consensus que la sévérité des chocs sur les marchés pétroliers tend à diminuer, ainsi que la dépendance des économies développées vis-à-vis de ces chocs. Les pays développés sont généralement les importateurs d'énergie et l'effet des chocs pétroliers sur les pays exportateurs de pétrole peut être différent, surtout s’il s’agit des pays dont la grande partie de l’exportation est le pétrole ou les produits pétroliers. En outre, l'orientation sur l'exportation des matières premières peut modifier la performance relative des modèles économétriques qui sont généralement utilisés pour les prévisions. La thèse étudie et développe des modèles de l'analyse structurelle et de la prévision à court terme d'une économie exportatrice de pétrole où les données russes sont utilisées pour toutes les applications empiriques. Le premier chapitre est consacré à la construction d'un modèle DSGE pour un pays exportateur de matières premières. Le modèle DSGE est estim...

Research paper thumbnail of Essais sur la prévision et modélisation d'une économie riche en ressources pétrolières

Il y a un consensus que la severite des chocs sur les marches petroliers tend a diminuer, ainsi q... more Il y a un consensus que la severite des chocs sur les marches petroliers tend a diminuer, ainsi que la dependance des economies developpees vis-a-vis de ces chocs. Les pays developpes sont generalement les importateurs d'energie et l'effet des chocs petroliers sur les pays exportateurs de petrole peut etre different, surtout s’il s’agit des pays dont la grande partie de l’exportation est le petrole ou les produits petroliers. En outre, l'orientation sur l'exportation des matieres premieres peut modifier la performance relative des modeles econometriques qui sont generalement utilises pour les previsions. La these etudie et developpe des modeles de l'analyse structurelle et de la prevision a court terme d'une economie exportatrice de petrole ou les donnees russes sont utilisees pour toutes les applications empiriques. Le premier chapitre est consacre a la construction d'un modele DSGE pour un pays exportateur de matieres premieres. Le modele DSGE est estim...

Research paper thumbnail of DSGE-based forecasting: What should our perspective be?

Voprosy Ekonomiki

The article compares the accuracy of point forecasts made with a structural dynamic stochastic ge... more The article compares the accuracy of point forecasts made with a structural dynamic stochastic general equilibrium model (DSGE) to those made with vector autoregressions estimated by OLS (VAR) and by Bayesian methods (BVAR). The main question addressed in the article is whether DSGE-based forecasts are as accurate as non-structural model ones. The comparison is made on the ground of mean squared forecast errors. The results show that the forecasting ability of the DSGE model is in general inferior to that of the BVAR. However, the difference is not critical. Moreover, for some variables and forecasting horizons, the DSGE model produces the forecast with the lowest error among all three models in question.

Research paper thumbnail of Forecasting Russian Macroeconomic Indicators with BVAR

SSRN Electronic Journal, 2000

This paper evaluates the forecast performance of Bayesian vector autoregressions (BVARs) on Russi... more 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.

Research paper thumbnail of Are commodity price shocks important? A Bayesian estimation of a DSGE model for Russia

International Journal of Computational Economics and Econometrics, 2014

Research paper thumbnail of Forecasting Russian Macroeconomic Indicators with BVAR

RePEc: Research Papers in Economics, 2015

This paper evaluates the forecast performance of Bayesian vector autoregressions (BVARs) on Russi... more 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.

Research paper thumbnail of Macroeconomic Forecasting with a Litterman's BVAR Model

This paper compares the forecasting performance of random walk, frequentist vector autoregression... more This paper compares the forecasting performance of random walk, frequentist vector autoregression (VAR), and Bayesian vector autoregression with Minnesota prior (BVAR) models on quarterly Russian data sample running from 1995 to 2014. Maximal number of variables included in the model is equal to 14 that requires an endogenous search of optimal shrinkage hyperparameter. The search procedure follows [Banbura et al., 2010; Bloor, Matheson, 2011].According to the selection method the shrinkage hyperparameter equates the forecasting quality of the frequentist VAR and BVAR for the minimal considered dimension of the model (three variables). For any dimension of the BVAR model the optimal shrinkage hyperparameter is robust to considered functions of relative forecasting accuracy.We show that the BVAR provides a more accurate forecast than the frequentist VAR on the studied sample. For key macro indicators (the industrial production index, consumer priceindex and the interbank interest rate), forecasting horizons, and all model sizes, the mean squared error of the BVAR is lower than that of the frequentist VAR. Moreover, the results show that the forecast made using the BVAR is more precise than the forecast made using random walk model for the CPI and using white noise model for the interbank rate. However, the BVAR cannot beat the random walk while forecasting the industrial production index.

Research paper thumbnail of Essays on forecasting and modelling an energy-based economy

Il y a un consensus que la sévérité des chocs sur les marchés pétroliers tend à diminuer, ainsi q... more Il y a un consensus que la sévérité des chocs sur les marchés pétroliers tend à diminuer, ainsi que la dépendance des économies développées vis-à-vis de ces chocs. Les pays développés sont généralement les importateurs d'énergie et l'effet des chocs pétroliers sur les pays exportateurs de pétrole peut être différent, surtout s’il s’agit des pays dont la grande partie de l’exportation est le pétrole ou les produits pétroliers. En outre, l'orientation sur l'exportation des matières premières peut modifier la performance relative des modèles économétriques qui sont généralement utilisés pour les prévisions. La thèse étudie et développe des modèles de l'analyse structurelle et de la prévision à court terme d'une économie exportatrice de pétrole où les données russes sont utilisées pour toutes les applications empiriques. Le premier chapitre est consacré à la construction d'un modèle DSGE pour un pays exportateur de matières premières. Le modèle DSGE est estim...

Research paper thumbnail of Essais sur la prévision et modélisation d'une économie riche en ressources pétrolières

Il y a un consensus que la severite des chocs sur les marches petroliers tend a diminuer, ainsi q... more Il y a un consensus que la severite des chocs sur les marches petroliers tend a diminuer, ainsi que la dependance des economies developpees vis-a-vis de ces chocs. Les pays developpes sont generalement les importateurs d'energie et l'effet des chocs petroliers sur les pays exportateurs de petrole peut etre different, surtout s’il s’agit des pays dont la grande partie de l’exportation est le petrole ou les produits petroliers. En outre, l'orientation sur l'exportation des matieres premieres peut modifier la performance relative des modeles econometriques qui sont generalement utilises pour les previsions. La these etudie et developpe des modeles de l'analyse structurelle et de la prevision a court terme d'une economie exportatrice de petrole ou les donnees russes sont utilisees pour toutes les applications empiriques. Le premier chapitre est consacre a la construction d'un modele DSGE pour un pays exportateur de matieres premieres. Le modele DSGE est estim...

Research paper thumbnail of DSGE-based forecasting: What should our perspective be?

Voprosy Ekonomiki

The article compares the accuracy of point forecasts made with a structural dynamic stochastic ge... more The article compares the accuracy of point forecasts made with a structural dynamic stochastic general equilibrium model (DSGE) to those made with vector autoregressions estimated by OLS (VAR) and by Bayesian methods (BVAR). The main question addressed in the article is whether DSGE-based forecasts are as accurate as non-structural model ones. The comparison is made on the ground of mean squared forecast errors. The results show that the forecasting ability of the DSGE model is in general inferior to that of the BVAR. However, the difference is not critical. Moreover, for some variables and forecasting horizons, the DSGE model produces the forecast with the lowest error among all three models in question.

Research paper thumbnail of Forecasting Russian Macroeconomic Indicators with BVAR

SSRN Electronic Journal, 2000

This paper evaluates the forecast performance of Bayesian vector autoregressions (BVARs) on Russi... more 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.

Research paper thumbnail of Are commodity price shocks important? A Bayesian estimation of a DSGE model for Russia

International Journal of Computational Economics and Econometrics, 2014