José Luis Montiel Olea, Mikkel Plagborg-Møller, Eric Qian, Christian K. Wolf
arXiv 15 May 2024 · Econometrics · publishedEconometrica (2026) · 25 citations (OpenAlex)
arXiv:2405.09509 · PDF · DOI · OpenAlex · Extracted main text
We consider impulse response inference in a locally misspecified vector autoregression (VAR) model. The conventional local projection (LP) confidence interval has correct coverage even when the misspecification is so large that it can be detected with probability approaching 1. This result follows from a "double robustness" property analogous to that of popular partially linear regression estimators. In contrast, the conventional VAR confidence interval with short-to-moderate lag length can severely undercover, even for misspecification that is small, economically plausible, and difficult to detect statistically. There is no free lunch: the VAR confidence interval has robust coverage only if the lag length is so large that the interval is as wide as the LP interval.
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| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Ramey, Valerie A (2016) Macroeconomic Shocks and Their Propagation | 1.000 | 6 | 3 | 100% |
| 2 | Lutz Kilian and Helmut Lütkepohl Structural Vector Autoregressive Analysis | 1.000 | 5 | 4 | 100% |
| 3 | Dake Li and Mikkel Plagborg-Møller and Christian K. Wolf (2024) Local projections vs.\ VARs: Lessons from thousands of DGPs self | 0.928 | 4 | 3 | 100% |
| 4 | Frank Schorfheide (2005) VAR forecasting under misspecification | 0.928 | 4 | 3 | 100% |
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| 7 | Montiel Olea, José Luis and Plagborg-Møller, Mikkel (2021) Local Projection Inference Is Simpler and More Robust Than You Think | 0.737 | 3 | 2 | 100% |
| 8 | Ke-Li Xu Local Projection Based Inference under General Conditions | 0.737 | 3 | 2 | 100% |
| 9 | Armstrong, Timothy B. and Kolesár, Michal (2021) Sensitivity analysis using approximate moment condition models | 0.644 | 2 | 2 | 100% |
| 10 | Chernozhukov, Victor and Escanciano, Juan Carlos and Ichimura, Hideh… (2022) Locally Robust Semiparametric Estimation | 0.644 | 2 | 2 | 100% |
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