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Identification through Heterogeneity

Author

Listed:
  • Thorsten Drautzburg

    (Federal Reserve Bank of Philadelphia)

  • Pooyan Amir-Ahmadi

    (University of Illinois at Urbana-Champaign)

Abstract

Set identification in Bayesian vector autoregression (VARs) is becoming increasingly popular while facing recent criticism about potentially unwanted prior dominance and underrepresented bounds of the identified set. This can lead to biased inference even in large samples. Common estimation strategies in high dimensions or with tight restrictions can prove to be highly inefficient or even practically infeasible. We propose to include micro data on heterogeneous entities for the estimation and identification of vector autoregressions to achieve sharper inference. First, we provide conditions when imposing a simple ranking of impulse responses will sharpen inference in bivariate and trivariate VARS. Importantly, we show that this sharpening also applies to variables not subject to ranking restrictions. Second, we develop two types of inference to address recent criticism: (i) A prior-robust posterior over the bounds of the identified set and (ii) a fully Bayesian sampling algorithm that allows us to efficiently include an agnostic prior over the non-identifiable parameters. Third, we apply our methodology to US data to identify productivity news and defense spending shocks. We find that under both algorithms the bounds of the identified sets shrink substantially under heterogeneity restrictions relative to standard sign restrictions.

Suggested Citation

  • Thorsten Drautzburg & Pooyan Amir-Ahmadi, 2017. "Identification through Heterogeneity," 2017 Meeting Papers 1087, Society for Economic Dynamics.
  • Handle: RePEc:red:sed017:1087
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    1. Blanchard, Olivier Jean & Quah, Danny, 1989. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," American Economic Review, American Economic Association, vol. 79(4), pages 655-673, September.
    2. Roberto Perotti, 2008. "In Search of the Transmission Mechanism of Fiscal Policy," NBER Chapters, in: NBER Macroeconomics Annual 2007, Volume 22, pages 169-226, National Bureau of Economic Research, Inc.
    3. 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.
    4. Christopher J. Nekarda & Valerie A. Ramey, 2011. "Industry Evidence on the Effects of Government Spending," American Economic Journal: Macroeconomics, American Economic Association, vol. 3(1), pages 36-59, January.
    5. Jonas E. Arias & Juan Rubio-Ramirez & Daniel F. Waggoner, 2013. "Inference Based on SVARs Identied with Sign and Zero Restrictions: Theory and Applications," Working Papers 2013-24, FEDEA.
    6. Juan F. Rubio-Ramírez & Daniel F. Waggoner & Tao Zha, 2010. "Structural Vector Autoregressions: Theory of Identification and Algorithms for Inference," Review of Economic Studies, Oxford University Press, vol. 77(2), pages 665-696.
    7. Giacomini, Raffaella & Kitagawa, Toru, 2014. "Inference about Non-Identified SVARs," CEPR Discussion Papers 10287, C.E.P.R. Discussion Papers.
    8. Inoue, Atsushi & Kilian, Lutz, 2013. "Inference on impulse response functions in structural VAR models," Journal of Econometrics, Elsevier, vol. 177(1), pages 1-13.
    9. 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.
    10. Fama, Eugene F. & French, Kenneth R., 1997. "Industry costs of equity," Journal of Financial Economics, Elsevier, vol. 43(2), pages 153-193, February.
    11. Emily Anderson & Atsushi Inoue & Barbara Rossi, 2016. "Heterogeneous Consumers and Fiscal Policy Shocks," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 48(8), pages 1877-1888, December.
    12. Robert B. Barsky & Eric R. Sims, 2012. "Information, Animal Spirits, and the Meaning of Innovations in Consumer Confidence," American Economic Review, American Economic Association, vol. 102(4), pages 1343-1377, June.
    13. Olivier Blanchard & Roberto Perotti, 2002. "An Empirical Characterization of the Dynamic Effects of Changes in Government Spending and Taxes on Output," The Quarterly Journal of Economics, Oxford University Press, vol. 117(4), pages 1329-1368.
    14. Faust, Jon, 1998. "The robustness of identified VAR conclusions about money," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 49(1), pages 207-244, December.
    15. Francis DiTraglia & Camilo García-Jimeno, 2016. "A Framework for Eliciting, Incorporating, and Disciplining Identification Beliefs in Linear Models," NBER Working Papers 22621, National Bureau of Economic Research, Inc.
    16. 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.
    17. 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.
    18. 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.
    19. Blanchard, Oliver & Cerutti, Eugenio & SUmmers, Lawrence, 2015. "Inflation and Activity - Two Explorations and Their Monetary Policy Implications," Working Paper Series 15-070, Harvard University, John F. Kennedy School of Government.
    20. John G. Fernald, 2012. "A quarterly, utilization-adjusted series on total factor productivity," Working Paper Series 2012-19, Federal Reserve Bank of San Francisco.
    21. Hyungsik Roger Moon & Frank Schorfheide, 2012. "Bayesian and Frequentist Inference in Partially Identified Models," Econometrica, Econometric Society, vol. 80(2), pages 755-782, March.
    22. Pooyan Amir Ahmadi & Harald Uhlig, 2015. "Sign Restrictions in Bayesian FaVARs with an Application to Monetary Policy Shocks," NBER Working Papers 21738, National Bureau of Economic Research, Inc.
    23. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," Review of Economic Studies, Oxford University Press, vol. 72(3), pages 821-852.
    24. 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.
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    Cited by:

    1. Christian Matthes & Felipe Schwartzman, 2019. "The Demand Origins of Business Cycles," 2019 Meeting Papers 1122, Society for Economic Dynamics.
    2. Alessio Volpicella, 2019. "SVARs Identification through Bounds on the Forecast Error Variance," Working Papers 890, Queen Mary University of London, School of Economics and Finance.
    3. Thorsten Drautzburg, 2020. "A narrative approach to a fiscal DSGE model," Quantitative Economics, Econometric Society, vol. 11(2), pages 801-837, May.
    4. Laura Liu & Christian Matthes & Katerina Petrova, 2022. "Monetary Policy Across Space and Time," Advances in Econometrics, in: Essays in Honour of Fabio Canova, volume 44, pages 37-64, Emerald Group Publishing Limited.
    5. Christian Matthes & Felipe Schwartzman, 2019. "What Do Sectoral Dynamics Tell Us About the Origins of Business Cycles?," Working Paper 19-9, Federal Reserve Bank of Richmond.
    6. Francis DiTraglia & Camilo García-Jimeno, 2016. "A Framework for Eliciting, Incorporating, and Disciplining Identification Beliefs in Linear Models," NBER Working Papers 22621, National Bureau of Economic Research, Inc.

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    More about this item

    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
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E62 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Fiscal Policy; Modern Monetary Theory

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