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Joint Inference and Counterfactual experimentation for Impulse Response Functions by Local Projections

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  • Oscar Jorda

    (Department of Economics, University of California Davis)

Abstract

This paper provides three measures of the uncertainty associated to an impulse response path: (1) conditional confidence bands which isolate the uncertainty of individual response coefficients given the temporal path experienced up to that point; (2) response percentile bounds} which provide bounds on the universe of permissible paths at a given probability level; and (3) Wald tests of joint significance and joint cumulative significance. These results rely on general assumptions for the joint distribution of the system's impulse responses. Given this distribution, the paper then shows how to construct counterfactual experiments formally; provides a test on the likelihood of observing the counterfactual; and derives the distribution of the system's responses conditional on the counterfactual. The paper then derives the asymptotic joint distribution of structural impulse responses identified by either short- or long-run recursive assumptions and estimated by local projections (Jorda, 2005). An application to a two country system implements all of these new methods.

Suggested Citation

  • Oscar Jorda, 2007. "Joint Inference and Counterfactual experimentation for Impulse Response Functions by Local Projections," Working Papers 107, University of California, Davis, Department of Economics.
  • Handle: RePEc:cda:wpaper:107
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    File URL: https://repec.dss.ucdavis.edu/files/DeE2cUjEqK9M2AHjZ3N6DKua/06-24.pdf
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    References listed on IDEAS

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    1. Cochrane, John H., 1998. "What do the VARs mean? Measuring the output effects of monetary policy," Journal of Monetary Economics, Elsevier, vol. 41(2), pages 277-300, April.
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    3. Carl E. Walsh, 2003. "Monetary Theory and Policy, 2nd Edition," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232316, December.
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    5. Kuersteiner, Guido M., 2002. "Efficient Iv Estimation For Autoregressive Models With Conditional Heteroskedasticity," Econometric Theory, Cambridge University Press, vol. 18(3), pages 547-583, June.
    6. Sims, Christopher A., 1992. "Interpreting the macroeconomic time series facts : The effects of monetary policy," European Economic Review, Elsevier, vol. 36(5), pages 975-1000, June.
    7. Kuersteiner, Guido M., 2001. "Optimal instrumental variables estimation for ARMA models," Journal of Econometrics, Elsevier, vol. 104(2), pages 359-405, September.
    8. Oscar Jorda & Sharon Kozicki, 2006. "Projection Minimum Distance: An Estimator for Dynamic Macroeconomic Models," Working Papers 623, University of California, Davis, Department of Economics.
    9. Keating, John W., 1996. "Structural information in recursive VAR orderings," Journal of Economic Dynamics and Control, Elsevier, vol. 20(9-10), pages 1557-1580.
    10. Oscar Jorda & Sharon Kozicki, 2006. "Projection Minimum Distance: An Estimator for Dynamic Macroeconomic Models," Working Papers 154, University of California, Davis, Department of Economics.
    11. Lucas, Robert Jr, 1976. "Econometric policy evaluation: A critique," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 1(1), pages 19-46, January.
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