2023/07 | LEM Working Paper Series | ||||||||||||||||
Identification of Vector Autoregressive Models with Nonlinear Contemporaneous Structure |
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Francesco Cordoni, Nicolas Doremus and Alessio Moneta |
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Keywords | |||||||||||||||||
Structural VAR models; Causal Discovery; Nonlinearity; Additive Noise Models; Impulse response functions.
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JEL Classifications | |||||||||||||||||
C32, C52, E52
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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.
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