Bootstrapping Structural VARs: Avoiding a Potential Bias in Confidence Intervals for Impulse Response Functions
AbstractConstructing bootstrap confidence intervals for impulse response functions (IRFs) from structural vector autoregression (SVAR) models has become standard practice in empirical macroeconomic research. The accuracy of such confidence intervals can deteriorate severely, however, if the bootstrap IRFs are biased. In this paper, we document an apparently common source of bias in the estimation of the VAR error covariance matrix. The bias is easily corrected with a straightforward scale adjustment. This bias is often unrecognized because it only affects the bootstrap estimates of the error variance, not the original OLS estimates. Nevertheless, as we illustrate here, analytically, with sampling experiments, and in an example from the literature, the bootstrap error variance bias can have significant distorting effects on bootstrap IRF confidence intervals even if the original IRF estimate relies on unbiased parameter estimates.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 23503.
Date of creation: Feb 2010
Date of revision:
impulse response function; structural VAR; bias; bootstrap;
Other versions of this item:
- Phillips, Kerk L. & Spencer, David E., 2011. "Bootstrapping structural VARs: Avoiding a potential bias in confidence intervals for impulse response functions," Journal of Macroeconomics, Elsevier, vol. 33(4), pages 582-594.
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
- E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-07-03 (All new papers)
- NEP-ECM-2010-07-03 (Econometrics)
- NEP-ETS-2010-07-03 (Econometric Time Series)
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- Davidson, Russell & MacKinnon, James G., 1993. "Estimation and Inference in Econometrics," OUP Catalogue, Oxford University Press, number 9780195060119.
- Christopher A. Sims & Tao Zha, 1994.
"Error Bands for Impulse Responses,"
Cowles Foundation Discussion Papers
1085, Cowles Foundation for Research in Economics, Yale University.
- Runkle, David E, 1987. "Vector Autoregressions and Reality: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(4), pages 454, October.
- John B. Taylor, 1999. "Monetary Policy Rules," NBER Books, National Bureau of Economic Research, Inc, number tayl99-1, May.
- Jeremy Berkowitz & Lutz Kilian, 2000.
"Recent developments in bootstrapping time series,"
Taylor & Francis Journals, vol. 19(1), pages 1-48.
- Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 1997.
"Monetary policy shocks: what have we learned and to what end?,"
Working Paper Series, Macroeconomic Issues
WP-97-18, Federal Reserve Bank of Chicago.
- Christiano, Lawrence J. & Eichenbaum, Martin & Evans, Charles L., 1999. "Monetary policy shocks: What have we learned and to what end?," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 2, pages 65-148 Elsevier.
- Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 1998. "Monetary Policy Shocks: What Have We Learned and to What End?," NBER Working Papers 6400, National Bureau of Economic Research, Inc.
- Runkle, David E, 1987. "Vector Autoregressions and Reality," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(4), pages 437-42, October.
- Blanchard, Olivier Jean & Quah, Danny, 1989.
"The Dynamic Effects of Aggregate Demand and Supply Disturbances,"
American Economic Review,
American Economic Association, vol. 79(4), pages 655-73, September.
- Tom Doan, . "BQDODRAWS: RATS procedure to implement Monte Carlo draws from a VAR with Blanchard-Quah factorization," Statistical Software Components RTS00030, Boston College Department of Economics.
- Tom Doan, . "RATS programs to replicate Blanchard and Quah AER 1989," Statistical Software Components RTZ00017, Boston College Department of Economics.
- Olivier Jean Blanchard & Danny Quah, 1990. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," NBER Working Papers 2737, National Bureau of Economic Research, Inc.
- Olivier Jean Blanchard & Danny Quah, 1988. "The Dynamic Effects of Aggregate Demand and Supply Disturbance," Working papers 497, Massachusetts Institute of Technology (MIT), Department of Economics.
- Kilian, Lutz & Chang, Pao-Li, 2000. "How accurate are confidence intervals for impulse responses in large VAR models?," Economics Letters, Elsevier, vol. 69(3), pages 299-307, December.
- Lutz Kilian, 1998. "Small-Sample Confidence Intervals For Impulse Response Functions," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 218-230, May.
- Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2006.
"Assessing Structural VARs,"
NBER Working Papers
12353, National Bureau of Economic Research, Inc.
- Peters, S C & Freedman, D A, 1984. "Some Notes on the Bootstrap in Regression Problems," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 406-09, October.
- David E. Runkle, 1987. "Vector autoregressions and reality," Staff Report 107, Federal Reserve Bank of Minneapolis.
- Filippo Lechthaler & Lisa Leinert, 2012. "Moody Oil - What is Driving the Crude Oil Price?," CER-ETH Economics working paper series 12/168, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
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