The New Palgrave Dictionary of Economics

2018 Edition
| Editors: Macmillan Publishers Ltd

Impulse Response Function

  • Helmut Lütkepohl
Reference work entry
DOI: https://doi.org/10.1057/978-1-349-95189-5_2410

Abstract

Impulse response functions are useful for studying the interactions between variables in a vector autoregressive model. They represent the reactions of the variables to shocks hitting the system. It is often not clear, however, which shocks are relevant for studying specific economic problems. Therefore structural information has to be used to specify meaningful shocks. Structural vector autoregressive models and the estimation of impulse responses are discussed and extensions to models with cointegrated variables or nonlinear features are considered.

Keywords

Bayesian methods Bootstrap Cointegrated variables Cointegration Conditional moment profiles Dynamic multipliers Forecast error impulse responses Generalized impulse responses Impulse response functions Integrated variables Least squares Linear models Maximum likelihood Nonlinear time series models Orthogonalized impulse responses Simultaneous equations models Structural impulse responses Structural vector autoregressions Vector autoregressions Wold causal ordering Wold moving average 

JEL Classifications

C32 
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Bibliography

  1. Amisano, G., and C. Giannini. 1997. Topics in structural VAR econometrics. 2nd ed. Berlin: Springer.CrossRefGoogle Scholar
  2. Benkwitz, A., H. Lütkepohl, and M. Neumann. 2000. Problems related to bootstrapping impulse responses of autoregressive processes. Econometric Reviews 19: 69–103.CrossRefGoogle Scholar
  3. Benkwitz, A., H. Lütkepohl, and J. Wolters. 2001. Comparison of bootstrap confidence intervals for impulse responses of German monetary systems. Macroeconomic Dynamics 5: 81–100.CrossRefGoogle Scholar
  4. Blanchard, O., and D. Quah. 1989. The dynamic effects of aggregate demand and supply disturbances. American Economic Review 79: 655–673.Google Scholar
  5. Canova, F., and G. De Nicoló. 2003. On the sources of business cycles in the G-7. Journal of International Economics 59: 77–100.CrossRefGoogle Scholar
  6. Christiano, L., M. Eichenbaum, and C. Evans. 1996. The effects of monetary policy shocks: Evidence from the flow of funds. The Review of Economics and Statistics 78: 16–34.CrossRefGoogle Scholar
  7. Gallant, A., P. Rossi, and G. Tauchen. 1993. Nonlinear dynamic structures. Econometrica 61: 871–907.CrossRefGoogle Scholar
  8. Kilian, L. 1998. Small-sample confidence intervals for impulse response functions. The Review of Economics and Statistics 80: 218–230.CrossRefGoogle Scholar
  9. King, R., C. Plosser, J. Stock, and M. Watson. 1991. Stochastic trends and economic fluctuations. American Economic Review 81: 819–840.Google Scholar
  10. Koop, G. 1992. Aggregate shocks and macroeconomic fluctuations: A Bayesian approach. Journal of Applied Econometrics 7: 395–411.CrossRefGoogle Scholar
  11. Koop, G., M. Pesaran, and S. Potter. 1996. Impulse response analysis in nonlinear multivariate models. Journal of Econometrics 74: 119–147.CrossRefGoogle Scholar
  12. Lütkepohl, H. 1988. Asymptotic distribution of the moving average coefficients of an estimated vector autoregressive process. Econometric Theory 4: 77–85.CrossRefGoogle Scholar
  13. Lütkepohl, H. 1990. Asymptotic distributions of impulse response functions and forecast error variance decompositions of vector autoregressive models. The Review of Economics and Statistics 72: 116–125.CrossRefGoogle Scholar
  14. Lütkepohl, H. 2005. New introduction to multiple time series analysis. Berlin: Springer.CrossRefGoogle Scholar
  15. Lütkepohl, H., and P. Saikkonen. 1997. Impulse response analysis in infinite order cointegrated vector autoregressive processes. Journal of Econometrics 81: 127–157.CrossRefGoogle Scholar
  16. Pesaran, M., and Y. Shin. 1998. Generalized impulse response analysis in linear multivariate models. Economics Letters 58: 17–29.CrossRefGoogle Scholar
  17. Sims, C. 1980. Macroeconomics and reality. Econometrica 48: 1–48.CrossRefGoogle Scholar
  18. Sims, C., and T. Zha. 1999. Error bands for impulse responses. Econometrica 67: 1113–1155.CrossRefGoogle Scholar
  19. Uhlig, H. 2005. What are the effects of monetary policy on output? Results from an agnostic identification procedure. Journal of Monetary Economics 52: 381–419.CrossRefGoogle Scholar

Copyright information

© Macmillan Publishers Ltd. 2018

Authors and Affiliations

  • Helmut Lütkepohl
    • 1
  1. 1.