Arbeitspapier

Choosing between different time-varying volatility models for structural vector autoregressive analysis

The performance of information criteria and tests for residual heteroskedasticity 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. Heteroskedasticity 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.

Language
Englisch

Bibliographic citation
Series: DIW Discussion Papers ; No. 1672

Classification
Wirtschaft
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Subject
structural vector autoregression
identification via heteroskedasticity
conditional heteroskedasticity
smooth transition
Markov switching
GARCH

Event
Geistige Schöpfung
(who)
Lütkepohl, Helmut
Schlaak, Thore
Event
Veröffentlichung
(who)
Deutsches Institut für Wirtschaftsforschung (DIW)
(where)
Berlin
(when)
2017

Handle
Last update
10.03.2025, 11:42 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Lütkepohl, Helmut
  • Schlaak, Thore
  • Deutsches Institut für Wirtschaftsforschung (DIW)

Time of origin

  • 2017

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