Choosing Between Different Time‐Varying Volatility Models for Structural Vector Autoregressive Analysis

Helmut Lütkepohl · Thore Schlaak

33 citations0/0 files storedOxford Bulletin of Economics and Statistics

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Financial Risk and Volatility Modeling Monetary Policy and Economic Impact Market Dynamics and Volatility

Abstract

Abstract The performance of information criteria and tests for residual heteroscedasticity for choosing between different models for time‐varying volatility in the context of structural vector autoregressive analysis is investigated. Although it can be difficult to find the true volatility model with the selection criteria, using them is recommended because they can reduce the mean squared error of impulse response estimates substantially relative to a model that is chosen arbitrarily based on the personal preferences of a researcher. Heteroscedasticity tests are found to be useful tools for deciding whether time‐varying volatility is present but do not discriminate well between different types of volatility changes. The selection methods are illustrated by specifying a model for the global market for crude oil.

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References

1982Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation 2009Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market 2005Time Varying Structural Vector Autoregressions and Monetary Policy n.d.Multivariate GARCH models: a survey 2005A forecast comparison of volatility models: does anything beat a GARCH(1,1)?2002SMOOTH TRANSITION AUTOREGRESSIVE MODELS — A SURVEY OF RECENT DEVELOPMENTS 2017Structural Vector Autoregressive Analysis 2003Identification Through Heteroskedasticity

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