How Reliable Are Local Projection Estimators of Impulse Responses?

By Lutz Kilian, Yun-jung Kim. Review of Economics and Statistics, 2011

147 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/ede5adbce147ea7db7518fedee8dfe5e5891246a

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Citations in the corpus

If the Fed Sneezes, Who Catches a Cold? (2017, methodology): “18In a small sample like ours, there is no guarantee that impulse responses for the same variables obtained from the BVAR and from (2) would be similar – see e.g., Kilian and Kim (2011).”
Forecast Error Variance Decompositions with Local Projections (2019, methodology): “The properties of impulse responses estimated with these methods are well studied (see, e.g., Coibion 2012; Kilian and Kim 2011), but little is known about how one can reliably estimate the quantitative significance of shocks in the singleequation framework.”
Local Projection Inference Is Simpler and More Robust Than You Think (2020, methodology): “Kilian and Kim (2011) and Brugnolini (2018) present simulation studies comparing AR inference and LP inference.”
Bias in Local Projections (2020, unknown): “Our paper is related to work by Kilian and Kim (2011), who study the coverage probabilities for confidence intervals for LP estimators.”
The Role of Oil Price Shocks in Causing U.S. Recessions (2014, methodology): “We focus on the NFCI because of all indicators of U.S. financial stress this index is available for the longest time span, but Table 2 also includes results for the Federal Reserve Board Staff Financial Stress Index, which is available since 1988 (see Hubrich and Tetlow 2012).”
NONLINEARITIES IN THE OIL PRICE–OUTPUT RELATIONSHIP (2010, unknown): “This would require a consistent estimate of the structural impact multiplier matrix from an external structural model such as the model proposed by Kilian and Vigfusson [see, e.g., Jordà (2009) and Kilian and Kim (2011), equations (5)–(7)].”
Joint Confidence Sets for Structural Impulse Responses (2016, unknown): “Simulation evidence on the finite-sample accuracy of these confidence bands is discussed in Kilian and Kim (2011) and Lütkepohl et al. (2015).”
Local Projections vs. VARs: Lessons From Thousands of DGPs (2021, methodology): “Our large-scale model set-up differs from prior simulation studies of LP and VAR meth-ods, which have considered at most a handful of DGPs. Examples here include Jordà (2005), Meier (2005), Kilian & Kim (2011), Brugnolini (2018), Choi & Chudik (2019), Austin (2020), and Bruns & Lütkepohl (2022).”
Non-Linear Exchange Rate Pass-Through in Emerging Markets (2016, methodology): “LPs are a flexible semi-parametric technique to estimate impulse responses. which directly estimate a sequence of linear projections of the future value of the dependent variable on the current information set (Kilian and Kim, 2011).”