arXiv 14 Dec 2022 · Econometrics
arXiv:2212.07263 · PDF · DOI · OpenAlex · Extracted main text
Statistical identification of possibly non-fundamental SVARMA models requires structural errors: (i) to be an i.i.d process, (ii) to be mutually independent across components, and (iii) each of them must be non-Gaussian distributed. Hence, provided the first two requisites, it is crucial to evaluate the non-Gaussian identification condition. We address this problem by relating the non-Gaussian dimension of structural errors vector to the rank of a matrix built from the higher-order spectrum of reduced-form errors. This makes our proposal robust to the roots location of the lag polynomials, and generalizes the current procedures designed for the restricted case of a causal structural VAR model. Simulation exercises show that our procedure satisfactorily estimates the number of non-Gaussian components.
appendix boundary found by none_found · 100% of the source is main text. Read the extracted text to check this.
The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Guay, A (2021) Identification of structural vector autoregressions through higher unconditional moments | 1.000 | 16 | 6 | 100% |
| 2 | Maxand, S (2020) Identification of independent structural shocks in the presence of multiple gaussian components | 1.000 | 8 | 4 | 100% |
| 3 | Nordhausen, K., Oja, H., Tyler, D. E., and Virta, J (2017) Asymptotic and bootstrap tests for the dimension of the non-gaussian subspace | 1.000 | 7 | 4 | 100% |
| 4 | Kleibergen, F. and Paap, R (2006) Generalized reduced rank tests using the singular value decomposition | 0.874 | 6 | 2 | 100% |
| 5 | Amengual, D., Fiorentini, G., and Sentana, E (2022) Moment tests of independent components | 0.874 | 5 | 2 | 100% |
| 6 | Velasco, C (2022) Identification and estimation of structural varma models using higher order dynamics | 0.874 | 5 | 2 | 100% |
| 7 | Blanchard, O. J. and Quah, D (1989) The dynamic effects of aggregate demand and supply disturbances | 0.811 | 4 | 2 | 100% |
| 8 | Blanchard, O. and Perotti, R (2002) An empirical characterization of the dynamic effects of changes in government spending and taxes on output | 0.811 | 4 | 2 | 100% |
| 9 | Gouriéroux, C., Monfort, A., and Renne, J.-P (2020) Identification and estimation in non-fundamental structural varma models | 0.811 | 4 | 2 | 100% |
| 10 | Comon, P (1994) Independent component analysis, a new concept? | 0.737 | 3 | 2 | 100% |
Showing the top 10 of 56 scored citations.