Forecasting Russia's Key Macroeconomic Indicators with the VAR-LASSO Model

Nikita Fokin and Andrey Polbin

Russian Journal of Money and Finance, 2019, vol. 78, issue 2, 67-93

Abstract: This paper examines an application of the VAR-LASSO model to Russia's key macroeconomic indicators: GDP, household consumption, fixed asset investment, exports, imports, and the rouble real exchange rate, along with oil prices (as an exogenous variable). The slowdown in the Russian economy following the 2008-2009 crisis is modelled as a structural break in the unconditional mean of growth rates of the time series under examination. The model is estimated with the assumption of a common growth rate for GDP, consumption, investment, exports and imports (any discrepancies in actual growth rates are due to changing oil prices and other shocks), which provides a solid foundation for balanced medium-term forecasts using an econometric specification that factors in this constraint. The model exhibits fairly good predictive power when pseudo real-time forecasts are benchmarked against the forecast by the Ministry of Economic Development and the forecast given by the BVAR model in Pestova and Mamonov (2016b), as well as against the best (based on the BIC criterion) VAR(1) model and the classical ARIMA model. The estimated model is used to study functions for impulse responses to oil price shocks and to build scenario-driven forecasts for 2019-2024.

Keywords: vector autoregression; machine learning; regularised models; GDP forecast; Russian economy; curse of dimensionality; oil prices (search for similar items in EconPapers)
JEL-codes: C53 C55 E21 E22 E27 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:bkr:journl:v:78:y:2019:i:2:p:67-93

DOI: 10.31477/rjmf.201901.67

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