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Identifying Proxy VARs with Restrictions on the Forecast Error Variance

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  • Härtl, Tilmann

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  • Härtl, Tilmann, 2022. "Identifying Proxy VARs with Restrictions on the Forecast Error Variance," VfS Annual Conference 2022 (Basel): Big Data in Economics 264071, Verein für Socialpolitik / German Economic Association.
    • Handle: RePEc:zbw:vfsc22:264071
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    1. N. Bloom, 2016. "Fluctuations in uncertainty," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 4.
    2. Karel Mertens & Morten O. Ravn, 2013. "The Dynamic Effects of Personal and Corporate Income Tax Changes in the United States," American Economic Review, American Economic Association, vol. 103(4), pages 1212-1247, June.
    3. Sungbae An & Frank Schorfheide, 2007. "Bayesian Analysis of DSGE Models—Rejoinder," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 211-219.
    4. Montiel Olea, José Luis & Nesbit, James, 2021. "(Machine) learning parameter regions," Journal of Econometrics, Elsevier, vol. 222(1), pages 716-744.
    5. Barsky, Robert B. & Sims, Eric R., 2011. "News shocks and business cycles," Journal of Monetary Economics, Elsevier, vol. 58(3), pages 273-289.
    6. Brüggemann, Ralf & Jentsch, Carsten & Trenkler, Carsten, 2016. "Inference in VARs with conditional heteroskedasticity of unknown form," Journal of Econometrics, Elsevier, vol. 191(1), pages 69-85.
    7. Caldara, Dario & Fuentes-Albero, Cristina & Gilchrist, Simon & Zakrajšek, Egon, 2016. "The macroeconomic impact of financial and uncertainty shocks," European Economic Review, Elsevier, vol. 88(C), pages 185-207.
    8. Neville Francis & Michael T. Owyang & Jennifer E. Roush & Riccardo DiCecio, 2014. "A Flexible Finite-Horizon Alternative to Long-Run Restrictions with an Application to Technology Shocks," The Review of Economics and Statistics, MIT Press, vol. 96(4), pages 638-647, October.
    9. Alessandri, Piergiorgio & Mumtaz, Haroon, 2019. "Financial regimes and uncertainty shocks," Journal of Monetary Economics, Elsevier, vol. 101(C), pages 31-46.
    10. Christina D. Romer & David H. Romer, 2010. "The Macroeconomic Effects of Tax Changes: Estimates Based on a New Measure of Fiscal Shocks," American Economic Review, American Economic Association, vol. 100(3), pages 763-801, June.
    11. Ivana Komunjer & Serena Ng, 2011. "Dynamic Identification of Dynamic Stochastic General Equilibrium Models," Econometrica, Econometric Society, vol. 79(6), pages 1995-2032, November.
    12. Carsten Jentsch & Kurt G. Lunsford, 2022. "Asymptotically Valid Bootstrap Inference for Proxy SVARs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(4), pages 1876-1891, October.
    13. Bassett, William F. & Chosak, Mary Beth & Driscoll, John C. & Zakrajšek, Egon, 2014. "Changes in bank lending standards and the macroeconomy," Journal of Monetary Economics, Elsevier, vol. 62(C), pages 23-40.
    14. Nadav Ben Zeev & Evi Pappa, 2017. "Chronicle of a War Foretold: The Macroeconomic Effects of Anticipated Defence Spending Shocks," Economic Journal, Royal Economic Society, vol. 127(603), pages 1568-1597, August.
    15. Michele Piffer & Maximilian Podstawski, 2018. "Identifying Uncertainty Shocks Using the Price of Gold," Economic Journal, Royal Economic Society, vol. 128(616), pages 3266-3284, December.
    16. Minchul Shin & Molin Zhong, 2020. "A New Approach to Identifying the Real Effects of Uncertainty Shocks," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 367-379, April.
    17. Sungbae An & Frank Schorfheide, 2007. "Bayesian Analysis of DSGE Models," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 113-172.
    18. 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.
    19. Kilian,Lutz & Lütkepohl,Helmut, 2018. "Structural Vector Autoregressive Analysis," Cambridge Books, Cambridge University Press, number 9781107196575, October.
    20. Harald Uhlig, 2004. "What moves GNP?," Econometric Society 2004 North American Winter Meetings 636, Econometric Society.
    21. Harald Uhlig, 2004. "Do Technology Shocks Lead to a Fall in Total Hours Worked?," Journal of the European Economic Association, MIT Press, vol. 2(2-3), pages 361-371, 04/05.
    22. 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.
    23. Simon Gilchrist & Egon Zakrajsek, 2012. "Credit Spreads and Business Cycle Fluctuations," American Economic Review, American Economic Association, vol. 102(4), pages 1692-1720, June.
    24. Carsten Jentsch & Kurt G. Lunsford, 2019. "The Dynamic Effects of Personal and Corporate Income Tax Changes in the United States: Comment," American Economic Review, American Economic Association, vol. 109(7), pages 2655-2678, July.
    25. Nadav Ben Zeev & Evi Pappa, 2017. "Chronicle of a War Foretold: The Macroeconomic Effects of Anticipated Defence Spending Shocks," Economic Journal, Royal Economic Society, vol. 127(603), pages 1568-1597, August.
    26. Raffaella Giacomini, 2013. "The relationship between DSGE and VAR models," CeMMAP working papers CWP21/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    27. James H. Stock & Mark W. Watson, 2012. "Disentangling the Channels of the 2007-2009 Recession," NBER Working Papers 18094, National Bureau of Economic Research, Inc.
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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

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