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A Narrative Approach to a Fiscal DSGE Model

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  • Thorsten Drautzburg

    (Federal Reserve Bank of Philadelphia)

Abstract

DSGE models are used for analyzing policy and the sources of business cycles. A competing approach uses VARs that are partially identified using, for example, narrative shock measures and are often viewed as imposing fewer restrictions on the data. Narrative shocks are identified non-structurally through information external to particular models. This uses non-structural narrative shock measures to inform the structural estimation of DSGE models. Since fiscal policy has received much recent attention but the foundations of the fiscal side of DSGE models are less well studied than their monetary building block, fiscal DSGE models are a particularly promising application. Preliminary results from a standard medium-scale DSGE model support this argument: Structurally identified monetary shocks line up well with narrative measures, whereas government spending shocks do not. Extending the model to include distortionary taxes and more general fiscal policy processes, I find that model implied labor tax shocks line up well with narrative tax shocks. Including different narrative shock measures affects parameter identification and implied measures such as fiscal multipliers.

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  • Thorsten Drautzburg, 2014. "A Narrative Approach to a Fiscal DSGE Model," 2014 Meeting Papers 791, Society for Economic Dynamics.
  • Handle: RePEc:red:sed014:791
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    as
    1. Christina D. Romer & David H. Romer, 2004. "A New Measure of Monetary Shocks: Derivation and Implications," American Economic Review, American Economic Association, vol. 94(4), pages 1055-1084, September.
    2. Fabio Canova & Filippo Ferroni & Christian Matthes, 2014. "Choosing The Variables To Estimate Singular Dsge Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(7), pages 1099-1117, November.
    3. 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.
    4. Henning Bohn, "undated". "Budget Balance Through Revenue or Spending Adjustments ? Some Historical Evidence for the United States (Reprint 013)," Rodney L. White Center for Financial Research Working Papers 03-91, Wharton School Rodney L. White Center for Financial Research.
    5. Valerie A. Ramey, 2011. "Identifying Government Spending Shocks: It's all in the Timing," The Quarterly Journal of Economics, Oxford University Press, vol. 126(1), pages 1-50.
    6. Richard Clarida & Jordi Galí & Mark Gertler, 2000. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," The Quarterly Journal of Economics, Oxford University Press, vol. 115(1), pages 147-180.
    7. 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.
    8. Sims, Christopher A, 1998. "Comment on Glenn Rudebusch's "Do Measures of Monetary Policy in a VAR Make Sense?"," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 933-941, November.
    9. Kuttner, Kenneth N., 2001. "Monetary policy surprises and interest rates: Evidence from the Fed funds futures market," Journal of Monetary Economics, Elsevier, vol. 47(3), pages 523-544, June.
    10. 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.
    11. Thorsten Drautzburg & Harald Uhlig, 2015. "Fiscal Stimulus and Distortionary Taxation," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 18(4), pages 894-920, October.
    12. Marco Del Negro & Frank Schorfheide, 2009. "Monetary Policy Analysis with Potentially Misspecified Models," American Economic Review, American Economic Association, vol. 99(4), pages 1415-1450, September.
    13. James H. Stock & Mark W. Watson, 2012. "Disentangling the Channels of the 2007-09 Recession," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 43(1 (Spring), pages 81-156.
    14. Refet S. Gürkaynak & Brian Sack & Eric Swanson, 2005. "The Sensitivity of Long-Term Interest Rates to Economic News: Evidence and Implications for Macroeconomic Models," American Economic Review, American Economic Association, vol. 95(1), pages 425-436, March.
    15. V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2004. "A Critique of Structural VARs Using Real Business Cycle Theory," Levine's Bibliography 122247000000000518, UCLA Department of Economics.
    16. Lawrence Christiano & Martin Eichenbaum & Sergio Rebelo, 2011. "When Is the Government Spending Multiplier Large?," Journal of Political Economy, University of Chicago Press, vol. 119(1), pages 78-121.
    17. 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.
    18. John Geweke, 1999. "Using simulation methods for bayesian econometric models: inference, development,and communication," Econometric Reviews, Taylor & Francis Journals, vol. 18(1), pages 1-73.
    19. Hedibert Lopes & Nicholas Polson, 2014. "Bayesian Instrumental Variables: Priors and Likelihoods," Econometric Reviews, Taylor & Francis Journals, vol. 33(1-4), pages 100-121.
    20. Rudebusch, Glenn D, 1998. "Do Measures of Monetary Policy in a VAR Make Sense? A Reply," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 943-948, November.
    21. Neville Francis & Valerie A. Ramey, 2009. "Measures of per Capita Hours and Their Implications for the Technology-Hours Debate," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(6), pages 1071-1097, September.
    22. Waggoner, Daniel F. & Zha, Tao, 2012. "Confronting model misspecification in macroeconomics," Journal of Econometrics, Elsevier, vol. 171(2), pages 167-184.
    23. Gunter Coenen & Roland Straub & Mathias Trabandt, 2012. "Fiscal Policy and the Great Recession in the Euro Area," American Economic Review, American Economic Association, vol. 102(3), pages 71-76, May.
    24. Lanne, Markku & Meitz, Mika & Saikkonen, Pentti, 2017. "Identification and estimation of non-Gaussian structural vector autoregressions," Journal of Econometrics, Elsevier, vol. 196(2), pages 288-304.
    25. Marco Del Negro & Frank Schorfheide, 2004. "Priors from General Equilibrium Models for VARS," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(2), pages 643-673, May.
    26. 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.
    27. Wieland, Volker & Cwik, Tobias & Müller, Gernot J. & Schmidt, Sebastian & Wolters, Maik, 2012. "A new comparative approach to macroeconomic modeling and policy analysis," Journal of Economic Behavior & Organization, Elsevier, vol. 83(3), pages 523-541.
    28. Leeper, Eric M. & Plante, Michael & Traum, Nora, 2010. "Dynamics of fiscal financing in the United States," Journal of Econometrics, Elsevier, vol. 156(2), pages 304-321, June.
    29. Barbara Rossi & Sarah Zubairy, 2011. "What Is the Importance of Monetary and Fiscal Shocks in Explaining U.S. Macroeconomic Fluctuations?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(6), pages 1247-1270, September.
    30. JonasD.M. Fisher & Ryan Peters, 2010. "Using Stock Returns to Identify Government Spending Shocks," Economic Journal, Royal Economic Society, vol. 120(544), pages 414-436, May.
    31. Pablo A. Guerron-Quintana, 2010. "What you match does matter: the effects of data on DSGE estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(5), pages 774-804.
    32. 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.
    33. Jonas E. Arias & Dario Caldara & Juan F. Rubio-Ramírez, 2014. "The Systematic Component of Monetary Policy in SVARs: An Agnostic Identification Procedure," Working Papers 2014-13, FEDEA.
    34. Bohn, Henning, 1991. "Budget balance through revenue or spending adjustments? : Some historical evidence for the United States," Journal of Monetary Economics, Elsevier, vol. 27(3), pages 333-359, June.
    35. John Geweke, 1999. "Using Simulation Methods for Bayesian Econometric Models," Computing in Economics and Finance 1999 832, Society for Computational Economics.
    36. John G. Fernald, 2012. "A quarterly, utilization-adjusted series on total factor productivity," Working Paper Series 2012-19, Federal Reserve Bank of San Francisco.
    37. Hyungsik Roger Moon & Frank Schorfheide, 2012. "Bayesian and Frequentist Inference in Partially Identified Models," Econometrica, Econometric Society, vol. 80(2), pages 755-782, March.
    38. Rudebusch, Glenn D, 1998. "Do Measures of Monetary Policy in a VAR Make Sense?," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 907-931, November.
    39. 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.
    40. Thorsten Drautzburg, 2013. "Entrepreneurial tail risk: implications for employment dynamics," Working Papers 13-45, Federal Reserve Bank of Philadelphia.
    41. Edward Herbst & Frank Schorfheide, 2014. "Sequential Monte Carlo Sampling For Dsge Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(7), pages 1073-1098, November.
    42. Hollmayr, Josef & Matthes, Christian, 2014. "Dynamics of Monetary-Fiscal Interaction under Learning," Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100609, Verein für Socialpolitik / German Economic Association.
    43. Zha, Tao, 1999. "Block recursion and structural vector autoregressions," Journal of Econometrics, Elsevier, vol. 90(2), pages 291-316, June.
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    Cited by:

    1. Antolin-Diaz, Juan & Rubio-Ramirez, Juan F., 2016. "Narrative Sign Restrictions for SVARs," FRB Atlanta Working Paper 2016-16, Federal Reserve Bank of Atlanta, revised 01 Oct 2017.
    2. Antolin-Diaz, Juan & Rubio-Ramirez, Juan F., 2016. "Narrative Sign Restrictions for SVARs," FRB Atlanta Working Paper 2016-16, Federal Reserve Bank of Atlanta, revised 01 Oct 2017.
    3. Thorsten Drautzburg & Jesús Fernández-Villaverde & Pablo Guerrón-Quintana, 2017. "Political Distribution Risk and Aggregate Fluctuations," NBER Working Papers 23647, National Bureau of Economic Research, Inc.
    4. Jentsch, Carsten & Lunsford, Kurt G., 2016. "Proxy SVARs : asymptotic theory, bootstrap inference, and the effects of income tax changes in the United States," Working Papers 16-10, University of Mannheim, Department of Economics.

    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
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E62 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Fiscal Policy

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