Abstract
This paper provides a vector autoregression model with an additional regularization problem similar to the Hodrick–Prescott filter problem to model a single, i.e., balanced, growth rate of the structural component of the main macroeconomic indicators of the Russian economy. This model includes the real GDP without government expenditure, the real household consumption, real fixed capital investment, the real exports, the real imports, and the real effective ruble exchange rate. Oil prices are exogenously included in the model. It is assumed that the GDP without government expenditure and its components have a balanced potential growth rate. The actual discrepancies in the time series are explained by the different long-term oil price multipliers and by the stochastic shocks. Based on the proposed model, we calculate the impacts of the oil price shocks and the structural component on the GDP without government expenditure and its components.
Similar content being viewed by others
REFERENCES
R. J. Hodrick and E. C. Prescott, “Postwar US business cycles: An empirical investigation,” J. Money, Credit, Bank. 29 (1), p. 1–16 (1997).
M. Baxter and R. G. King, “Measuring business cycles: Approximate band-pass filters for economic time series,” Rev. Econ. Stat., 81 (4), 575–593 (1999).
S. Beveridge and C. R. Nelson, “A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the ‘business cycle’,” J. Monetary Econ. 7 (2), 151–174 (1981).
P. St-Amant and S. van Norden, “Measurement of the Output Gap: A discussion of recent research at the Bank of Canada,” Technical Report No. 79 (Bank of Canada, Ottawa, 1997).
S. Sinelnikov-Murylev, S. Drobyshevskii, and M. Kazakova, “Decomposition of GDP growth rates in Russia in 1999–2014,” Ekon. Polit. No. 5, 7–37 (2014).
N. Vashchelyuk, A. Zubarev, and P. Trunin, Determination of the Output Gap for the Russian Economy (Russ. Presidential Acad. of Nation. Econ. Public Administration, Moscow, 2016), 83 p. [in Russian]. https://doi.org/10.2139/ssrn.2753995
N. V. Orlova and S. K. Egiev, “Structural factors of a slowdown in Russian economic growth,” Vopr. Ekon., No. 12, 69–84 (2015).
N. V. Orlova and N. A. Lavrova, “Potential growth as a reflection of Russian economy perspectives,” Vopr. Ekon., No. 4, 5–20 (2019).
M. Villani, “Steady-state priors for vector autoregressions,” J. Appl. Econometrics 24 (4), 630–650 (2009).
M. Clements and D. Hendry, Forecasting Economic Time Series (Cambridge Univ. Press, Cambridge, 1998).
R. G. King, C. I. Plosser, J. H. Stock, and M. W. Watson, “Stochastic trends and economic fluctuations,” Am. Econ. Rev. 81 (4), 819–40 (1991).
A. V. Polbin, “Estimation of the impact of oil price shocks on the Russian economy in the vector error correction model (VECM),” Vopr. Ekon., No. 10, 27–49 (2017).
N. P. Pilnik, S. A. Radionov, and I. P. Stankevich, “Generalized multi-product decomposition of elements of the use of Russia’s GDP,” Ekon. Zh. Vyssh. Shk. Ekon. 22 (2), 251–274 (2018).
K. Whelan, “A guide to US chain aggregated NIPA data,” Rev. Income Wealth 48 (2), 217–233 (2002).
A. V. Polbin and A. A. Skrobotov, “Testing for structural breaks in the long-run growth rate of the GDP of the Russian Federation,” Ekon. Zh. Vyssh. Shk. Ekon. 20 (4), 588–623 (2016).
Author information
Authors and Affiliations
Corresponding authors
Ethics declarations
The article was written on the basis of the RANEPA state assignment research programme.
Additional information
Translated by A. Muravnik
Rights and permissions
About this article
Cite this article
Polbin, A.V., Fokin, N.D. Econometric Modeling of the Balanced Potential Growth Rate of the Main Russian Macroeconomic Variables. Math Models Comput Simul 13, 244–253 (2021). https://doi.org/10.1134/S2070048221020125
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1134/S2070048221020125