Structural Vector Autoregressive Models with More Shocks than Variables Identified via Heteroskedasticity

Helmut Lütkepohl

No 1871, Discussion Papers of DIW Berlin from DIW Berlin, German Institute for Economic Research

Abstract: 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.

Keywords: Structural vector autoregression; identification through heteroskedasticity; structural shocks (search for similar items in EconPapers)
JEL-codes: C32 (search for similar items in EconPapers)
Pages: 10 p.
Date: 2020
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-ore
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