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Small-sample confidence intervals for multivariate impulse response functions at long horizons

Author

Listed:
  • Barbara Rossi

    (Department of Economics, Duke University, Durham, North Carolina, USA)

  • Elena Pesavento

    (Department of Economics, Emory University, Atlanta, Georgia, USA)

Abstract
Existing methods for constructing confidence bands for multivariate impulse response functions may have poor coverage at long lead times when variables are highly persistent. The goal of this paper is to propose a simple method that is not pointwise and that is robust to the presence of highly persistent processes. We use approximations based on local-to-unity asymptotic theory, and allow the horizon to be a fixed fraction of the sample size. We show that our method has better coverage properties at long horizons than existing methods, and may provide different economic conclusions in empirical applications. We also propose a modification of this method which has good coverage properties at both short and long horizons. Copyright © 2006 John Wiley & Sons, Ltd.

Suggested Citation

  • Barbara Rossi & Elena Pesavento, 2006. "Small-sample confidence intervals for multivariate impulse response functions at long horizons," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(8), pages 1135-1155.
  • Handle: RePEc:jae:japmet:v:21:y:2006:i:8:p:1135-1155
    DOI: 10.1002/jae.894
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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • F40 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - General

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