The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Sufficient information in structural VARs
Open accessAbstract
Necessary and sufficient conditions under which a VAR contains sufficient information to estimate the structural shocks are derived. On the basis of this theoretical result we propose two simple tests to detect informational deficiency and a procedure to amend a deficient VAR. A simulation based on a DSGE model with fiscal foresight suggests that our method correctly identifies and fixes the informational problem. In an empirical application, we show that a bivariate VAR including unemployment and labor productivity is informationally deficient. Once the relevant information is included into the model, technology shocks appear to be contractionary.
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Cites
Opening the black box: low-dimensional dynamics in high-dimensional recurrent neural networks
Sussillo, D., & Barak, O. (2013) · Neural Computation · doi:10.1162/neco_a_00409 · Cited by 575
Does Information Help Recovering Structural Shocks from past Observations?
Giannone, D., & Reichlin, L. (2006) · Journal of the European Economic Association · doi:10.1162/jeea.2006.4.2-3.455 · Cited by 133
Metadata
- Authors
- Forni, M., & Gambetti, L.
- Venue
- Journal of Monetary Economics
- Publisher
- Elsevier BV
- Published
- 2014-09
- Volume
- 66
- Pages
- 124-136
- ISSN
- 0304-3932 (ISSN-L)
- OpenAlex
- W2150863267
- Cited by
- 205
- References
- 2
- FWCI
- 39.15
- Type
- journal article
- Language
- en
- Open access
- green
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- Forni, M., & Gambetti, L. (2014). Sufficient information in structural VARs. Journal of Monetary Economics. https://doi.org/10.1016/j.jmoneco.2014.04.005
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
