IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

Comparing Hybrid DSGE Models

  • Alessia Paccagnini

    ()

This paper discusses the estimation of Dynamic Stochastic General Equilibrium (DSGE) models using hybrid models. These econometric tools provide the combination of an atheoretical statistical representation and the theoretical features of the DSGE model. A review of hybrid models presents the main aspects of these tools and why they are needed in the recent macroeconometric literature. Some of these models are compared to classical econometrics models (such as Vector Autoregressive, Factor Augmented VAR and Bayesian VAR) in a marginal data density analysis.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://dipeco.economia.unimib.it/repec/pdf/mibwpaper228.pdf
File Function: First version, 2012
Download Restriction: no

Paper provided by University of Milano-Bicocca, Department of Economics in its series Working Papers with number 228.

as
in new window

Length: 35
Date of creation: Dec 2012
Date of revision: Dec 2012
Handle: RePEc:mib:wpaper:228
Contact details of provider: Postal: Piazza Ateneo Nuovo, 1 Milano 20126
Phone: +39 02 6448 3089
Fax: +39 02 6448 3085
Web page: http://dipeco.economia.unimib.it
Email:


More information through EDIRC

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409 National Bureau of Economic Research, Inc.
  2. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
  3. John Geweke, 1998. "Using simulation methods for Bayesian econometric models: inference, development, and communication," Staff Report 249, Federal Reserve Bank of Minneapolis.
  4. Smets, Frank & Wouters, Rafael, 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach," CEPR Discussion Papers 6112, C.E.P.R. Discussion Papers.
  5. Theodoridis, Konstantinos, 2007. "Dynamic Stochastic General Equilibrium (DSGE) Priors for Bayesian Vector Autoregressive (BVAR) Models: DSGE Model Comparison," Cardiff Economics Working Papers E2007/15, Cardiff University, Cardiff Business School, Economics Section.
  6. Allan W. Gregory & Gregor W. Smith, 1991. "Calibration in Macroeconomics," Working Papers 826, Queen's University, Department of Economics.
  7. Sims, Christopher A, 2002. "Solving Linear Rational Expectations Models," Computational Economics, Society for Computational Economics, vol. 20(1-2), pages 1-20, October.
  8. Rubaszek, Michal & Skrzypczynski, Pawel, 2008. "On the forecasting performance of a small-scale DSGE model," International Journal of Forecasting, Elsevier, vol. 24(3), pages 498-512.
  9. Watson, Mark W, 1993. "Measures of Fit for Calibrated Models," Journal of Political Economy, University of Chicago Press, vol. 101(6), pages 1011-41, December.
  10. Lawrence J. Christiano & Martin Eichenbaum, 1990. "Current real business cycle theories and aggregate labor market fluctuations," Discussion Paper / Institute for Empirical Macroeconomics 24, Federal Reserve Bank of Minneapolis.
  11. Jesus Fernandez-Villaverde & Juan F. Rubio-Ramirez & Thomas J. Sargent, 2005. "A, B, C’s (And D’s) For Understanding VARS," PIER Working Paper Archive 05-018, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  12. Frank Smets & Raf Wouters, 2004. "Forecasting with a Bayesian DSGE Model: An Application to the Euro Area," Journal of Common Market Studies, Wiley Blackwell, vol. 42(4), pages 841-867, November.
  13. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, vol. 50(6), pages 1345-70, November.
  14. Banbura, Marta & Giannone, Domenico & Reichlin, Lucrezia, 2007. "Bayesian VARs with Large Panels," CEPR Discussion Papers 6326, C.E.P.R. Discussion Papers.
  15. Ghent, Andra C., 2009. "Comparing DSGE-VAR forecasting models: How big are the differences?," Journal of Economic Dynamics and Control, Elsevier, vol. 33(4), pages 864-882, April.
  16. Jushan Bai & Serena Ng, 2000. "Determining the Number of Factors in Approximate Factor Models," Boston College Working Papers in Economics 440, Boston College Department of Economics.
  17. Adolfson, Malin & Laséen, Stefan & Lindé, Jesper & Villani, Mattias, 2007. "Evaluating An Estimated New Keynesian Small Open Economy Model," Working Paper Series 203, Sveriges Riksbank (Central Bank of Sweden).
  18. Robert G. King, 2000. "The new IS-LM model : language, logic, and limits," Economic Quarterly, Federal Reserve Bank of Richmond, issue Sum, pages 45-103.
  19. Malley, Jim University of Glasgow & Woitek, Ulrich, 2009. "Technology shocks and aggregate fluctuations in an estimated hybrid RBC model," SIRE Discussion Papers 2009-18, Scottish Institute for Research in Economics (SIRE).
  20. Clarida, R. & Gali, J. & Gertler, M., 1998. "Monetary Policy Rules and Macroeconomic Stability: Evidence and some Theory," Working Papers 98-01, C.V. Starr Center for Applied Economics, New York University.
  21. S.G. Cecchetti & P. Lam & N.C. Mark, 2010. "The equity premium and the risk-free rate: matching the moments," Levine's Working Paper Archive 1396, David K. Levine.
  22. Ingram, Beth F. & Whiteman, Charles H., 1994. "Supplanting the 'Minnesota' prior: Forecasting macroeconomic time series using real business cycle model priors," Journal of Monetary Economics, Elsevier, vol. 34(3), pages 497-510, December.
  23. Francis X. Diebold & Lee E. Ohanian & Jeremy Berkowitz, 1998. "Dynamic equilibrium economies: a framework for comparing models and data," Staff Report 243, Federal Reserve Bank of Minneapolis.
  24. Altug, Sumru, 1989. "Time-to-Build and Aggregate Fluctuations: Some New Evidence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 30(4), pages 889-920, November.
  25. DeJong, David N. & Ingram, Beth F. & Whiteman, Charles H., 2000. "A Bayesian approach to dynamic macroeconomics," Journal of Econometrics, Elsevier, vol. 98(2), pages 203-223, October.
  26. Stelios Bekiros & Alessia Paccagnini, 2013. "On the predictability of time-varying VAR and DSGE models," Empirical Economics, Springer, vol. 45(1), pages 635-664, August.
  27. Peter N. Ireland, 1999. "A method for taking models to the data," Working Paper 9903, Federal Reserve Bank of Cleveland.
  28. Schorfheide, Frank & Sill, Keith & Kryshko, Maxym, 2010. "DSGE model-based forecasting of non-modelled variables," International Journal of Forecasting, Elsevier, vol. 26(2), pages 348-373, April.
  29. Consolo, Agostino & Favero, Carlo A. & Paccagnini, Alessia, 2009. "On the statistical identification of DSGE models," Journal of Econometrics, Elsevier, vol. 150(1), pages 99-115, May.
  30. Ali Dib & Mohamed Gammoudi & Kevin Moran, 2006. "Forecasting Canadian Time Series With the New-Keynesian Model," Working Papers Central Bank of Chile 382, Central Bank of Chile.
  31. Sargent, Thomas J, 1989. "Two Models of Measurements and the Investment Accelerator," Journal of Political Economy, University of Chicago Press, vol. 97(2), pages 251-87, April.
  32. Federico Ravenna, 2006. "Vector autoregressions and reduced form representations of DSGE models," Banco de Espa�a Working Papers 0619, Banco de Espa�a.
  33. Jean Boivin & Marc Giannoni, 2006. "DSGE Models in a Data-Rich Environment," NBER Working Papers 12772, National Bureau of Economic Research, Inc.
  34. Feve, Patrick & Langot, Francois, 1994. "The RBC Models through Statistical Inference: An Application with French Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 9(S), pages S11-35, Suppl. De.
  35. Sims, Christopher A & Zha, Tao, 1998. "Bayesian Methods for Dynamic Multivariate Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 949-68, November.
  36. Kirdan Lees & Troy Matheson & Christie Smith, 2007. "Open Economy Dsge-Var Forecasting And Policy Analysis: Head To Head With The Rbnz Published Forecasts," CAMA Working Papers 2007-05, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  37. Marco Maffezzoli, 2000. "Human Capital and International Real Business Cycles," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 3(1), pages 137-165.
  38. Marta Bańbura, 2008. "Large Bayesian VARs," 2008 Meeting Papers 334, Society for Economic Dynamics.
  39. Cooley, Thomas F & Prescott, Edward C, 1976. "Estimation in the Presence of Stochastic Parameter Variation," Econometrica, Econometric Society, vol. 44(1), pages 167-84, January.
  40. Chari, V.V. & Kehoe, Patrick J. & McGrattan, Ellen R., 2008. "Are structural VARs with long-run restrictions useful in developing business cycle theory?," Journal of Monetary Economics, Elsevier, vol. 55(8), pages 1337-1352, November.
  41. Kadiyala, K. Rao & Karlsson, Sune, 1994. "Numerical Aspects of Bayesian VAR-modeling," SSE/EFI Working Paper Series in Economics and Finance 12, Stockholm School of Economics.
  42. Marco Del Negro & Frank Schorfheide, 2002. "Priors from general equilibrium models for VARs," Working Paper 2002-14, Federal Reserve Bank of Atlanta.
  43. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 1997. "Monetary policy shocks: what have we learned and to what end?," Working Paper Series, Macroeconomic Issues WP-97-18, Federal Reserve Bank of Chicago.
  44. Kolasa, Marcin & Rubaszek, Michał & Skrzypczyński, Paweł, 2009. "Putting the New Keynesian DSGE model to the real-time forecasting test," Working Paper Series 1110, European Central Bank.
  45. Jesús Fernández-Villaverde, 2010. "The econometrics of DSGE models," SERIEs, Spanish Economic Association, vol. 1(1), pages 3-49, March.
  46. Christoffel, Kai & Warne, Anders & Coenen, Günter, 2010. "Forecasting with DSGE models," Working Paper Series 1185, European Central Bank.
  47. Canova, Fabio, 1995. "Sensitivity Analysis and Model Evaluation in Simulated Dynamic General Equilibrium Economies," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 36(2), pages 477-501, May.
  48. Rochelle M. Edge & Refet S. Gurkaynak, 2011. "How useful are estimated DSGE model forecasts?," Finance and Economics Discussion Series 2011-11, Board of Governors of the Federal Reserve System (U.S.).
  49. Litterman, Robert B, 1986. "Forecasting Accuracy of Alternative Techniques: A Comparison of U.S. Macroeconomic Forecasts: Comment," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 17-19, January.
  50. Finn E. Kydland & Edward C. Prescott, 1990. "The econometrics of the general equilibrium approach to business cycles," Staff Report 130, Federal Reserve Bank of Minneapolis.
  51. Nason, James M & Cogley, Timothy, 1994. "Testing the Implications of Long-Run Neutrality for Monetary Business Cycle Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 9(S), pages S37-70, Suppl. De.
  52. Fabio Canova & Luca Gambetti, 2004. "On the Time Variations of US Monetary Policy: Who is right?," Money Macro and Finance (MMF) Research Group Conference 2004 96, Money Macro and Finance Research Group.
  53. Lucas, Robert Jr., 1972. "Expectations and the neutrality of money," Journal of Economic Theory, Elsevier, vol. 4(2), pages 103-124, April.
  54. DeJong, David N & Ingram, Beth Fisher & Whiteman, Charles H, 1996. "A Bayesian Approach to Calibration," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 1-9, January.
  55. James H. Stock & Mark W. Watson, 2005. "Implications of Dynamic Factor Models for VAR Analysis," NBER Working Papers 11467, National Bureau of Economic Research, Inc.
  56. Canova, Fabio, 1994. "Statistical Inference in Calibrated Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 9(S), pages S123-44, Suppl. De.
  57. Frank Schorfheide, 2000. "Loss function-based evaluation of DSGE models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(6), pages 645-670.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:mib:wpaper:228. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Roberto Reale)

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

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

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.