Phillips, Kerk L. and Spencer, David E. (2010): Bootstrapping Structural VARs: Avoiding a Potential Bias in Confidence Intervals for Impulse Response Functions.
Download (258Kb) | Preview
Constructing 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.
|Item Type:||MPRA Paper|
|Original Title:||Bootstrapping Structural VARs: Avoiding a Potential Bias in Confidence Intervals for Impulse Response Functions|
|Keywords:||impulse response function; structural VAR; bias; bootstrap|
|Subjects:||C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models; Multiple Variables > C32 - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E32 - Business Fluctuations; Cycles
E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E37 - Forecasting and Simulation: Models and Applications
|Depositing User:||Kerk Phillips|
|Date Deposited:||26. Jun 2010 17:59|
|Last Modified:||12. Feb 2013 18:43|
Berkowitz, J. and L. Kilian, 2000, Recent developments in bootstrapping time series, Econometric Reviews 19, 1-48.
Christiano, L. J., M. Eichenbaum and C. L. Evans, 1999, Monetary policy shocks: What have we learned and to what end?” in: J. B. Taylor and M. Woodford, eds., Handbook of Macroeconomics, Vol. 1A (North –Holland, Amsterdam) 65-148.
Davidson, R. and J. G. MacKinnon, 1993, Estimation and Inference in Econometrics. (Oxford University Press, New York).
Freedman, D. A. and S. C. Peters, 1984, Bootstrapping a regression equation: Some empirical results, Journal of the American Statistical Association 79, 97-206.
Peters, S. C., and D. A. Freedman, 1984, Some notes on the bootstrap in regression problems, Journal of Business and Economics Statistics 2, 406-409.
Stine, R. A., 1987, Estimating properties of autoregressive forecasts, Journal of the American Statistical Association 82, 1072-1078.
Available Versions of this Item
- Bootstrapping Structural VARs: Avoiding a Potential Bias in Confidence Intervals for Impulse Response Functions. (deposited 26. Jun 2010 17:59) [Currently Displayed]