Arbeitspapier

Testing identification via heteroskedasticity in structural vector autoregressive models

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Tests for identification through heteroskedasticity in structural vector autoregressive analysis are developed for models with two volatility states where the time point of volatility change is known. The tests are Wald type tests for which only the unrestricted model including the covariance matrices of the two volatility states have to be estimated. The residuals of the model are assumed to be from the class of elliptical distributions which includes Gaussian models. The asymptotic null distributions of the test statistics are derived and simulations are used to explore their small sample properties. Two empirical examples illustrate the usefulness of the tests.

Language: Englisch

Bibliographic citation: Series: DIW Discussion Papers ; No. 1764

Classification: Wirtschaft
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

Subject: heteroskedasticity
structural identification
vector autoregressive process

Event: Geistige Schöpfung

(who): Lütkepohl, Helmut
Meitz, Mika
Netšunajev, Aleksei
Saikkonen, Pentti

Event: Veröffentlichung

(who): Deutsches Institut für Wirtschaftsforschung (DIW)

(where): Berlin

(when): 2018

Handle: http://hdl.handle.net/10419/183597

Last update: 10.03.2025, 11:44 AM CET

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Object type

Arbeitspapier

Associated

Lütkepohl, Helmut
Meitz, Mika
Netšunajev, Aleksei
Saikkonen, Pentti
Deutsches Institut für Wirtschaftsforschung (DIW)

Time of origin

2018

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