Identification of Vector Autoregressive Models with Nonlinear Contemporaneous Structure

Francesco Cordoni, Nicolas Doremus and Alessio Moneta

LEM Papers Series from Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy

Abstract: We propose a statistical identification procedure for recursive structural vector autoregressive (VAR) models that present a nonlinear dependence (at least) at the contemporaneous level. By applying and adapting results from the literature on causal discovery with continuous additive noise models, we show that, under certain conditions, a large class of structural VAR models is identifiable. We spell out these specific conditions and propose a scheme for the estimation of structural impulse response functions in a nonlinear setting. We assess the performance of this scheme in a simulation experiment. Finally, we apply it in a study on the effects of the macroeconomic shocks that propagate through the economy, allowing for asymmetry between responses from positive and negative impulses.

Keywords: Structural VAR models; Causal Discovery; Nonlinearity; Additive Noise Models; Impulse response functions. (search for similar items in EconPapers)
Date: 2023-01-27
New Economics Papers: this item is included in nep-ecm and nep-ets
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Journal Article: Identification of vector autoregressive models with nonlinear contemporaneous structure (2024)
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Persistent link: https://EconPapers.repec.org/RePEc:ssa:lemwps:2023/07

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