James A. Duffy, Sophocles Mavroeidis
arXiv 8 Apr 2024 · Econometrics
arXiv:2404.05349 · PDF · DOI · OpenAlex · Extracted main text
While it is widely recognised that linear (structural) VARs may fail to capture important aspects of economic time series, the use of nonlinear SVARs has to date been almost entirely confined to the modelling of stationary time series, because of a lack of understanding as to how common stochastic trends may be accommodated within nonlinear models. This has unfortunately circumscribed the range of series to which such models can be applied -- and/or required that these series be first transformed to stationarity, a potential source of misspecification -- and prevented the use of long-run identifying restrictions in these models. To address these problems, we develop a flexible class of additively time-separable nonlinear SVARs, which subsume models with threshold-type endogenous regime switching, both of the piecewise linear and smooth transition varieties. We extend the Granger--Johansen representation theorem to this class of models, obtaining conditions that specialise exactly to the usual ones when the model is linear. We further show that, as a corollary, these models are capable of supporting the same kinds of long-run identifying restrictions as are available in linearly cointegrated SVARs.
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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 | Duffy, J. A., S. Mavroeidis, and S. Wycherley (2023) Cointegration with Occasionally Binding Constraints, arXiv:2211.09604v2 self | 0.811 | 4 | 2 | 100% |
| 2 | Jungers, R. M (2009) The Joint Spectral Radius: theory and applications | 0.737 | 5 | 5 | 40% |
| 3 | Kristensen, D. and A. Rahbek (2010) Likelihood-based inference for cointegration with nonlinear error-correction | 0.737 | 3 | 2 | 100% |
| 4 | Blanchard, O. J. and D. Quah (1989) The dynamic effects of aggregate demand and supply disturbances | 0.644 | 2 | 2 | 100% |
| 5 | Hubrich, K. and T. Teräsvirta (2013) Thresholds and smooth transitions in vector autoregressive models, in | 0.644 | 2 | 2 | 100% |
| 6 | Johansen, S (1995) Likelihood-based Inference in Cointegrated Vector Autoregressive Models | 0.644 | 2 | 2 | 100% |
| 7 | King, R. G., C. I. Plosser, J. H. Stock, and M. W. Watson (1991) Stochastic Trends and Economic Fluctuations | 0.644 | 2 | 2 | 100% |
| 8 | Mavroeidis, S (2021) Identification at the zero lower bound self | 0.644 | 2 | 2 | 100% |
| 9 | Gourieroux, C., J. J. Laffont, and A. Monfort (1980) Coherency conditions in simultaneous linear equation models with endogenous switching regimes | 0.511 | 3 | 2 | 33% |
| 10 | Matzkin, R. L (2008) Identification in nonparametric simultaneous equations models | 0.405 | 10 | 2 | 10% |
Showing the top 10 of 28 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Estimation of a Dynamic Tobit Model with a Unit Root | 0.405 | 1 | 1 |