Dynamic Stochastic General Equilibrium Model with Multiple Trends and Structural Breaks

S. Ivashchenko
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引用次数: 1

Abstract

This paper constructs a dynamic stochastic general equilibrium model with various trends for each GDP by expenditure component and structural breaks. The model is estimated on the sample of 20 Russian time series from 2000Q1 to 2020Q4. It produces high-quality out-of-sample forecasts that outperform autoregressive models. Production efficiency shocks explain more than half of the variance of key variables (both conditional and unconditional). The version with structural breaks produces much better median-based forecasting measures and almost the same mean-based forecasting measures due to significant errors near structural breaks. Various inflation measures respond similarly to monetary policy shocks, but differently to other shocks.
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具有多趋势和结构断裂的动态随机一般均衡模型
本文构建了一个具有不同趋势的动态随机一般均衡模型。该模型对2000年第一季度至2020第四季度的20个俄罗斯时间序列样本进行了估计。它产生高质量的样本外预测,优于自回归模型。生产效率冲击解释了一半以上的关键变量(包括条件变量和无条件变量)的差异。具有结构断裂的版本产生了更好的基于中位数的预测方法,并且由于结构断裂附近的显着误差,几乎相同的基于均值的预测方法。各种通胀指标对货币政策冲击的反应相似,但对其他冲击的反应不同。
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Dynamic Stochastic General Equilibrium Model with Multiple Trends and Structural Breaks Comparison of Models for Growth-at-Risk Forecasting Modelling the Effects of Unconventional Monetary Policy in a Heterogeneous Monetary Union Forecasting Unemployment in Russia Using Machine Learning Methods A Real-Time Historical Database of Macroeconomic Indicators for Russia
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