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Identification and inference with ranking restrictions

Author

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  • Pooyan Amir‐Ahmadi
  • Thorsten Drautzburg
Abstract
We propose to add ranking restrictions on impulse‐responses to sign restrictions to narrow the identified set in vector autoregressions (VARs). Ranking restrictions come from micro data on heterogeneous industries in VARs, bounds on elasticities, or restrictions on dynamics. Using both a fully Bayesian conditional uniform prior and prior‐robust inference, we show that these restrictions help to identify productivity news shocks in the data. In the prior‐robust paradigm, ranking restrictions, but not sign restrictions alone, imply that news shocks raise output temporarily, but significantly. This holds both in an application with rankings in the form of heterogeneity restrictions and in another applications with slope restrictions as rankings. Ranking restrictions also narrow bounds on variance decompositions. For example, the bound of the contribution of news shocks to the forecast error variance of output narrows by about 30 pp at the one‐year horizon. While misspecification can be a concern with added restrictions, they are consistent with the data in our applications.

Suggested Citation

  • Pooyan Amir‐Ahmadi & Thorsten Drautzburg, 2021. "Identification and inference with ranking restrictions," Quantitative Economics, Econometric Society, vol. 12(1), pages 1-39, January.
    • Handle: RePEc:wly:quante:v:12:y:2021:i:1:p:1-39
    DOI: 10.3982/QE1277
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    References listed on IDEAS

    as
    1. Uhlig, Harald, 2005. "What are the effects of monetary policy on output? Results from an agnostic identification procedure," Journal of Monetary Economics, Elsevier, vol. 52(2), pages 381-419, March.
    2. Eleonora Granziera & Hyungsik Roger Moon & Frank Schorfheide, 2018. "Inference for VARs identified with sign restrictions," Quantitative Economics, Econometric Society, vol. 9(3), pages 1087-1121, November.
    3. Juan F. Rubio-Ramírez & Daniel F. Waggoner & Tao Zha, 2010. "Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 77(2), pages 665-696.
    4. Barsky, Robert B. & Sims, Eric R., 2011. "News shocks and business cycles," Journal of Monetary Economics, Elsevier, vol. 58(3), pages 273-289.
    5. Paul Beaudry & Franck Portier, 2006. "Stock Prices, News, and Economic Fluctuations," American Economic Review, American Economic Association, vol. 96(4), pages 1293-1307, September.
    6. Inoue, Atsushi & Kilian, Lutz, 2013. "Inference on impulse response functions in structural VAR models," Journal of Econometrics, Elsevier, vol. 177(1), pages 1-13.
    7. 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.
    8. Jing Cynthia Wu & Fan Dora Xia, 2016. "Measuring the Macroeconomic Impact of Monetary Policy at the Zero Lower Bound," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(2-3), pages 253-291, March.
    9. Fama, Eugene F. & French, Kenneth R., 1997. "Industry costs of equity," Journal of Financial Economics, Elsevier, vol. 43(2), pages 153-193, February.
    10. Jeffrey R. Campbell & Charles L. Evans & Jonas D.M. Fisher & Alejandro Justiniano, 2012. "Macroeconomic Effects of Federal Reserve Forward Guidance," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 43(1 (Spring), pages 1-80.
    11. Jonathan H. Wright, 2012. "What does Monetary Policy do to Long‐term Interest Rates at the Zero Lower Bound?," Economic Journal, Royal Economic Society, vol. 122(564), pages 447-466, November.
    12. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    13. Lutz Kilian & Daniel P. Murphy, 2012. "Why Agnostic Sign Restrictions Are Not Enough: Understanding The Dynamics Of Oil Market Var Models," Journal of the European Economic Association, European Economic Association, vol. 10(5), pages 1166-1188, October.
    14. Canova, Fabio & Nicolo, Gianni De, 2002. "Monetary disturbances matter for business fluctuations in the G-7," Journal of Monetary Economics, Elsevier, vol. 49(6), pages 1131-1159, September.
    15. Jonas E. Arias & Juan F. Rubio‐Ramírez & Daniel F. Waggoner, 2018. "Inference Based on Structural Vector Autoregressions Identified With Sign and Zero Restrictions: Theory and Applications," Econometrica, Econometric Society, vol. 86(2), pages 685-720, March.
    16. Frank Smets & Rafael Wouters, 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach," American Economic Review, American Economic Association, vol. 97(3), pages 586-606, June.
    17. Brendan Kline & Elie Tamer, 2016. "Bayesian inference in a class of partially identified models," Quantitative Economics, Econometric Society, vol. 7(2), pages 329-366, July.
    18. Arias, Jonas E. & Caldara, Dario & Rubio-Ramírez, Juan F., 2019. "The systematic component of monetary policy in SVARs: An agnostic identification procedure," Journal of Monetary Economics, Elsevier, vol. 101(C), pages 1-13.
    19. Christiane Baumeister & James D. Hamilton, 2015. "Sign Restrictions, Structural Vector Autoregressions, and Useful Prior Information," Econometrica, Econometric Society, vol. 83(5), pages 1963-1999, September.
    20. Z. I. Botev, 2017. "The normal law under linear restrictions: simulation and estimation via minimax tilting," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(1), pages 125-148, January.
    21. Uhlig, Harald, 1994. "What Macroeconomists Should Know about Unit Roots: A Bayesian Perspective," Econometric Theory, Cambridge University Press, vol. 10(3-4), pages 645-671, August.
    22. Ferre Graeve & Alexei Karas, 2014. "Evaluating Theories Of Bank Runs With Heterogeneity Restrictions," Journal of the European Economic Association, European Economic Association, vol. 12(4), pages 969-996, August.
    23. Lutz Kilian & Xiaoqing Zhou, 2018. "Structural Interpretation of Vector Autoregressions with Incomplete Identification: Revisiting the Role of Oil Supply and Demand Shocks: Comment," CESifo Working Paper Series 7166, CESifo.
    24. José Luis Montiel Olea & Mikkel Plagborg‐Møller, 2019. "Simultaneous confidence bands: Theory, implementation, and an application to SVARs," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(1), pages 1-17, January.
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    Cited by:

    1. Raffaella Giacomini & Toru Kitagawa & Matthew Read, 2021. "Identification and Inference Under Narrative Restrictions," Papers 2102.06456, arXiv.org.
    2. Emanuele Bacchiocchi & Toru Kitagawa, 2021. "A note on global identi?cation in structural vector autoregressions," CeMMAP working papers CWP03/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. De Graeve, Ferre & Schneider, Jan David, 2023. "Identifying sectoral shocks and their role in business cycles," Journal of Monetary Economics, Elsevier, vol. 140(C), pages 124-141.
    4. Matthew Read, 2022. "Algorithms for inference in SVARs identified with sign and zero restrictions [Identification and inference with ranking restrictions]," The Econometrics Journal, Royal Economic Society, vol. 25(3), pages 699-718.
    5. Drautzburg, Thorsten & Wright, Jonathan H., 2023. "Refining set-identification in VARs through independence," Journal of Econometrics, Elsevier, vol. 235(2), pages 1827-1847.
    6. Korobilis, Dimitris, 2022. "A new algorithm for structural restrictions in Bayesian vector autoregressions," European Economic Review, Elsevier, vol. 148(C).
    7. Matthew Read, 2022. "The Unit-effect Normalisation in Set-identified Structural Vector Autoregressions," RBA Research Discussion Papers rdp2022-04, Reserve Bank of Australia.
    8. Paul Levine & Joseph Pearlman & Alessio Volpicella & Bo Yang, 2022. "The Use and Mis-Use of SVARs for Validating DSGE Models," School of Economics Discussion Papers 0522, School of Economics, University of Surrey.
    9. Francis J. DiTraglia & Camilo Garcia-Jimeno, 2020. "A Framework for Eliciting, Incorporating, and Disciplining Identification Beliefs in Linear Models," Papers 2011.07276, arXiv.org.

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