Bulat Gafarov, Madina Karamysheva, Andrey Polbin, Anton Skrobotov
arXiv 3 Jul 2024 · Econometrics · 1 citations (OpenAlex)
arXiv:2407.03265 · PDF · DOI · OpenAlex · Extracted main text
Structural vector autoregressions are used to compute impulse response functions (IRF) for persistent data. Existing multiple-parameter inference requires cumbersome pretesting for unit roots, cointegration, and trends with subsequent stationarization. To avoid pretesting, we propose a novel dependent wild bootstrap procedure for simultaneous inference on IRF using local projections (LP) estimated in levels in possibly nonstationary and heteroscedastic SVARs. The bootstrap also allows efficient smoothing of LP estimates. We study IRF to US monetary policy identified using FOMC meetings count as an instrument for heteroscedasticity of monetary shocks. We validate our method using DSGE model simulations and alternative SVAR methods.
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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 | Montiel Olea, J. L. and M. Plagborg-Mller (2019) Simultaneous confidence bands: Theory, implementation, and an application to SVARs | 1.000 | 5 | 3 | 100% |
| 2 | Christiano, L. J., M. Eichenbaum, and C. L. Evans (1999) Monetary policy shocks: What have we learned and to what end? | 0.974 | 13 | 4 | 92% |
| 3 | Antolń-Dáz, J. and J. F. Rubio-Ramirez (2018) Narrative sign restrictions for SVARs | 0.874 | 12 | 2 | 100% |
| 4 | Andrews, D. W (1991) Heteroskedasticity and autocorrelation consistent covariance matrix estimation | 0.843 | 4 | 3 | 75% |
| 5 | Goncalves, S. and L. Kilian (2004) Bootstrapping autoregressions with conditional heteroskedasticity of unknown form | 0.843 | 3 | 3 | 100% |
| 6 | Jordà, Ò (2005) Estimation and inference of impulse responses by local projections | 0.843 | 3 | 3 | 100% |
| 7 | Montiel Olea, J. L. and M. Plagborg-Mller (2021) Local projection inference is simpler and more robust than you think | 0.843 | 3 | 3 | 100% |
| 8 | Inoue, A. and L. Kilian (2016) Joint confidence sets for structural impulse responses | 0.811 | 4 | 2 | 100% |
| 9 | Smets, F. and R. Wouters (2007) Shocks and frictions in US business cycles: A Bayesian DSGE approach | 0.811 | 4 | 2 | 100% |
| 10 | Sims, C. A., J. H. Stock, and M. W. Watson (1990) Inference in linear time series models with some unit roots | 0.794 | 8 | 3 | 50% |
Showing the top 10 of 76 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Projection Inference for Set-Identified SVARs | 0.405 | 1 | 1 |