用VAR-LASSO模型预测俄罗斯主要宏观经济指标

N. Fokin, A. Polbin
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引用次数: 5

摘要

本文将VAR-LASSO模型应用于俄罗斯的主要宏观经济指标:GDP、家庭消费、固定资产投资、出口、进口和卢布实际汇率,以及油价(作为外生变量)。2008-2009年危机后俄罗斯经济的放缓被建模为所研究的时间序列中无条件平均增长率的结构性断裂。该模型是在假设GDP、消费、投资、出口和进口的共同增长率的情况下进行估计的(实际增长率的任何差异都是由于油价变化和其他冲击造成的),这为使用考虑这一约束因素的计量经济学规范进行平衡的中期预测提供了坚实的基础。当以经济发展部的预测和Pestova和Mamonov (2016b)中的BVAR模型给出的预测为基准,以及以最佳(基于BIC标准)VAR(1)模型和经典ARIMA模型为基准时,该模型显示出相当好的预测能力。该估计模型用于研究油价冲击的脉冲响应函数,并建立2019-2024年的情景驱动预测。
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Forecasting Russia's Key Macroeconomic Indicators with the VAR-LASSO Model
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.
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