Arbeitspapier

Structural vector autoregressive models with more shocks than variables identified via heteroskedasticity

In conventional structural vector autoregressive (VAR) models it is assumed that there are at most as many structural shocks as there are variables in the model. It is pointed out that heteroskedasticity can be used to identify more shocks than variables. However, even if there is heteroskedasticity, the number of shocks that can be identified is limited. A number of results are provided that allow a researcher to assess how many shocks can be identified from specific forms of heteroskedasticity.

Language
Englisch

Bibliographic citation
Series: DIW Discussion Papers ; No. 1871

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 through heteroskedasticity
structural shocks

Event
Geistige Schöpfung
(who)
Lütkepohl, Helmut
Event
Veröffentlichung
(who)
Deutsches Institut für Wirtschaftsforschung (DIW)
(where)
Berlin
(when)
2020

Handle
Last update
10.03.2025, 11:42 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

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

Time of origin

  • 2020

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