IDEAS home Printed from https://ideas.repec.org/p/een/camaaa/2009-03.html
   My bibliography  Save this paper

A comparision of forecast, simple reduced-form models, and a DSGE model

Author

Listed:
  • Rochelle M. Edge
  • Michael T. Kiley
  • Jean-Philippe Laforte

Abstract

This paper considers the “real-time” forecast performance of the Federal Reserve staff, time-series models, and an estimated dynamic stochastic general equilibrium (DSGE) model - the Federal Reserve Board’s new Estimated, Dynamic, Optimization-based (Edo) model. We evaluate forecast performance using out-of-sample predictions from 1996 through 2005 - thereby examining over 70 forecasts presented to the Federal Open Market Committee (FOMC). Our analysis builds on previous real-time forecasting exercises along two dimensions. First, we consider time-series models, a structural DSGE model that has been employed to answer policy questions quite different from forecasting, and the forecasts produced by the staff at the Federal Reserve Board. In addition, we examine forecasting performance of our DSGE model at a relatively detailed level by separately considering the forecasts for various components of consumer expenditures and private investment. The results provide significant support to the notion that richly specified DSGE models belong in the forecasting toolbox of a central bank.

Suggested Citation

  • Rochelle M. Edge & Michael T. Kiley & Jean-Philippe Laforte, 2009. "A comparision of forecast, simple reduced-form models, and a DSGE model," CAMA Working Papers 2009-03, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Handle: RePEc:een:camaaa:2009-03
    as

    Download full text from publisher

    File URL: https://cama.crawford.anu.edu.au/sites/default/files/publication/cama_crawford_anu_edu_au/2021-06/3_edge_kiley_laforte_2009.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Michael T. Kiley, 2007. "A Quantitative Comparison of Sticky-Price and Sticky-Information Models of Price Setting," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 101-125, February.
    2. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2008. "The new area-wide model of the euro area: a micro-founded open-economy model for forecasting and policy analysis," Working Paper Series 944, European Central Bank.
    3. Christopher J. Erceg & Luca Guerrieri & Christopher Gust, 2006. "SIGMA: A New Open Economy Model for Policy Analysis," International Journal of Central Banking, International Journal of Central Banking, vol. 2(1), March.
    4. Sims, Christopher A., 2008. "Improving monetary policy models," Journal of Economic Dynamics and Control, Elsevier, vol. 32(8), pages 2460-2475, August.
    5. Jean-Philippe Laforte, 2007. "Pricing Models: A Bayesian DSGE Approach for the U.S. Economy," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 127-154, February.
    6. Malin Adolfson & Michael K. Andersson & Jesper Lindé & Mattias Villani & Anders Vredin, 2007. "Modern Forecasting Models in Action: Improving Macroeconomic Analyses at Central Banks," International Journal of Central Banking, International Journal of Central Banking, vol. 3(4), pages 111-144, December.
    7. Mark Gertler & Luca Sala & Antonella Trigari, 2008. "An Estimated Monetary DSGE Model with Unemployment and Staggered Nominal Wage Bargaining," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(8), pages 1713-1764, December.
    8. 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.
    9. Jordi Galí & Mark Gertler, 2007. "Macroeconomic Modeling for Monetary Policy Evaluation," Journal of Economic Perspectives, American Economic Association, vol. 21(4), pages 25-46, Fall.
    10. Faust, Jon & Wright, Jonathan H., 2009. "Comparing Greenbook and Reduced Form Forecasts Using a Large Realtime Dataset," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 468-479.
    11. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    12. Anne B. Koehler & Emily S. Murphree, 1988. "A Comparison of the Akaike and Schwarz Criteria for Selecting Model Order," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 37(2), pages 187-195, June.
    13. 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.
    14. Rochelle M. Edge & Michael T. Kiley & Jean-Philippe Laforte, 2007. "Documentation of the Research and Statistics Division’s estimated DSGE model of the U.S. economy: 2006 version," Finance and Economics Discussion Series 2007-53, Board of Governors of the Federal Reserve System (U.S.).
    15. repec:pri:cepsud:128sims is not listed on IDEAS
    16. Kirdan Lees & Troy Matheson & Christie Smith, 2007. "Open economy DSGE-VAR forecasting and policy analysis - head to head with the RBNZ published forecasts," Reserve Bank of New Zealand Discussion Paper Series DP2007/01, Reserve Bank of New Zealand.
    17. Marta Bańbura, 2008. "Large Bayesian VARs," 2008 Meeting Papers 334, Society for Economic Dynamics.
    18. Sims, Christopher A., 2008. "Improving monetary policy models," Journal of Economic Dynamics and Control, Elsevier, vol. 32(8), pages 2460-2475, August.
    19. Marta Banbura & Domenico Giannone & Lucrezia Reichlin, 2010. "Large Bayesian vector auto regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 71-92.
    20. Reifschneider, David L. & Stockton, David J. & Wilcox, David W., 1997. "Econometric models and the monetary policy process," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 47(1), pages 1-37, December.
    21. David H. Romer & Christina D. Romer, 2000. "Federal Reserve Information and the Behavior of Interest Rates," American Economic Review, American Economic Association, vol. 90(3), pages 429-457, June.
    22. Robert J. Gordon, 1998. "Foundations of the Goldilocks Economy: Supply Shocks and the Time-Varying NAIRU," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 29(2), pages 297-346.
    23. Kadiyala, K Rao & Karlsson, Sune, 1997. "Numerical Methods for Estimation and Inference in Bayesian VAR-Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(2), pages 99-132, March-Apr.
    24. Rochelle M. Edge & Michael T. Kiley & Jean-Philippe Laforte, 2005. "An estimated DSGE model of the US economy with an application to natural rate measures," Proceedings, Board of Governors of the Federal Reserve System (U.S.).
    25. Peter Tulip, 2005. "Has output become more predictable? changes in Greenbook forecast accuracy," Finance and Economics Discussion Series 2005-31, Board of Governors of the Federal Reserve System (U.S.).
    26. Fernandez-Villaverde, Jesus & Francisco Rubio-Ramirez, Juan, 2004. "Comparing dynamic equilibrium models to data: a Bayesian approach," Journal of Econometrics, Elsevier, vol. 123(1), pages 153-187, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Forecasting with DSGE models
      by Economic Logician in Economic Logic on 2009-07-28 19:23:00

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Michael T. Kiley & Jean-Philippe Laforte & Rochelle M. Edge, 2008. "The Sources of Fluctuations in Residential Investment: A View from a Policy-Oriented DSGE Model of the U.S. Economic," 2008 Meeting Papers 990, Society for Economic Dynamics.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rochelle M. Edge & Michael T. Kiley & Jean-Philippe Laforte, 2010. "A comparison of forecast performance between Federal Reserve staff forecasts, simple reduced-form models, and a DSGE model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 720-754.
    2. Maik H. Wolters, 2015. "Evaluating Point and Density Forecasts of DSGE Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(1), pages 74-96, January.
    3. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2010. "Forecasting with DSGE models," Working Paper Series 1185, European Central Bank.
    4. Bekiros, Stelios D. & Paccagnini, Alessia, 2014. "Bayesian forecasting with small and medium scale factor-augmented vector autoregressive DSGE models," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 298-323.
    5. Alessia Paccagnini, 2012. "Comparing Hybrid DSGE Models," Working Papers 228, University of Milano-Bicocca, Department of Economics, revised Dec 2012.
    6. Volker Wieland & Maik Wolters, 2011. "The diversity of forecasts from macroeconomic models of the US economy," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 47(2), pages 247-292, June.
    7. Bekiros Stelios & Paccagnini Alessia, 2015. "Estimating point and density forecasts for the US economy with a factor-augmented vector autoregressive DSGE model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(2), pages 107-136, April.
    8. Michael T. Kiley & Jean-Philippe Laforte & Rochelle M. Edge, 2008. "The Sources of Fluctuations in Residential Investment: A View from a Policy-Oriented DSGE Model of the U.S. Economic," 2008 Meeting Papers 990, Society for Economic Dynamics.
    9. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2015. "Realtime nowcasting with a Bayesian mixed frequency model with stochastic volatility," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(4), pages 837-862, October.
    10. Jordi Galí & Frank Smets & Rafael Wouters, 2012. "Unemployment in an Estimated New Keynesian Model," NBER Macroeconomics Annual, University of Chicago Press, vol. 26(1), pages 329-360.
    11. Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2015. "Prior Selection for Vector Autoregressions," The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 436-451, May.
    12. Drissi, Ramzi & Ghassan, Hassan B., 2018. "Sticky Price versus Sticky Information Price: Empirical Evidence in the New Keynesian Setting," MPRA Paper 93075, University Library of Munich, Germany, revised Apr 2019.
    13. Giannone, Domenico & Monti, Francesca & Reichlin, Lucrezia, 2016. "Exploiting the monthly data flow in structural forecasting," Journal of Monetary Economics, Elsevier, vol. 84(C), pages 201-215.
    14. Patrick C. Higgins, 2014. "GDPNow: A Model for GDP \"Nowcasting\"," FRB Atlanta Working Paper 2014-7, Federal Reserve Bank of Atlanta.
    15. Silvia Miranda-Agrippino & Giovanni Ricco, 2021. "The Transmission of Monetary Policy Shocks," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(3), pages 74-107, July.
    16. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2016. "Common Drifting Volatility in Large Bayesian VARs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(3), pages 375-390, July.
    17. Wieland, Volker & Wolters, Maik, 2013. "Forecasting and Policy Making," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 239-325, Elsevier.
    18. Karlsson, Sune, 2013. "Forecasting with Bayesian Vector Autoregression," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 791-897, Elsevier.
    19. Faust, Jon & Wright, Jonathan H., 2013. "Forecasting Inflation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 2-56, Elsevier.
    20. Mumtaz, Haroon & Theodoridis, Konstantinos, 2020. "Dynamic effects of monetary policy shocks on macroeconomic volatility," Journal of Monetary Economics, Elsevier, vol. 114(C), pages 262-282.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Lists

    This item is featured on the following reading lists, Wikipedia, or ReplicationWiki pages:
    1. Economic Logic blog

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:een:camaaa:2009-03. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Cama Admin (email available below). General contact details of provider: https://edirc.repec.org/data/asanuau.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.