Large Time-Varying Parameter Vars: A Non-Parametric Approach
63 Pages Posted: 28 Aug 2017
Date Written: June 16, 2017
In this paper we introduce a non-parametric estimation method for a large Vector Autoregression (VAR) with time-varying parameters. The estimators and their asymptotic distributions are available in closed form. This makes the method computationally efficient and capable of handling information sets as large as those typically handled by factor models and Factor Augmented VARs (FAVAR). When applied to the problem of forecasting key macroeconomic variables, the method outperforms constant parameter benchmarks and large (parametric) Bayesian VARs with time-varying parameters. The tool can also be used for structural analysis. As an example, we study the time-varying effects of oil price innovations on sectoral U.S. industrial output. We find that durable consumer goods and durable materials (which together account for slightly more than one fifth of total industrial output) play a key role in explaining the changing interaction between unexpected oil price increases and U.S. business cycle fluctuations.
Keywords: large VARs, time-varying parameters, non-parametric estimation, forecasting
JEL Classification: C14, C32, C53, C55
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