IDEAS home Printed from https://ideas.repec.org/a/eee/intfor/v31y2015i1p1-19.html
   My bibliography  Save this article

Forecasting using DSGE models with financial frictions

Author

Listed:
  • Kolasa, Marcin
  • Rubaszek, Michał

Abstract

This paper compares the quality of forecasts from DSGE models with and without financial frictions. We find that accounting for financial market imperfections does not result in a uniform improvement in the accuracy of point forecasts during non-crisis times, while the average quality of density forecast actually deteriorates. In contrast, adding frictions in the housing market proves very helpful during times of financial turmoil, outperforming both the frictionless benchmark and the alternative that incorporates financial frictions in the corporate sector. Moreover, we detect complementarities among the analyzed setups that can be exploited in the forecasting process.

Suggested Citation

  • Kolasa, Marcin & Rubaszek, Michał, 2015. "Forecasting using DSGE models with financial frictions," International Journal of Forecasting, Elsevier, vol. 31(1), pages 1-19.
    • Handle: RePEc:eee:intfor:v:31:y:2015:i:1:p:1-19
    DOI: 10.1016/j.ijforecast.2014.05.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0169207014000910
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijforecast.2014.05.001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Malin Adolfson & Jesper Linde & Mattias Villani, 2007. "Forecasting Performance of an Open Economy DSGE Model," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 289-328.
    2. Christiano, Lawrence J. & Trabandt, Mathias & Walentin, Karl, 2011. "Introducing financial frictions and unemployment into a small open economy model," Journal of Economic Dynamics and Control, Elsevier, vol. 35(12), pages 1999-2041.
    3. Alejandro Justiniano & Giorgio Primiceri & Andrea Tambalotti, 2011. "Investment Shocks and the Relative Price of Investment," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 14(1), pages 101-121, January.
    4. Matteo Iacoviello, 2005. "House Prices, Borrowing Constraints, and Monetary Policy in the Business Cycle," American Economic Review, American Economic Association, vol. 95(3), pages 739-764, June.
    5. 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.
    6. Kiyotaki, Nobuhiro & Moore, John, 1997. "Credit Cycles," Journal of Political Economy, University of Chicago Press, vol. 105(2), pages 211-248, April.
    7. Lawrence J. Christiano & Roberto Motto & Massimo Rostagno, 2003. "The Great Depression and the Friedman-Schwartz hypothesis," Proceedings, Federal Reserve Bank of Cleveland, pages 1119-1215.
    8. Marcin Kolasa & MichaŁ Rubaszek & PaweŁ SkrzypczyŃski, 2012. "Putting the New Keynesian DSGE Model to the Real-Time Forecasting Test," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(7), pages 1301-1324, October.
    9. Canova, Fabio, 2014. "Bridging DSGE models and the raw data," Journal of Monetary Economics, Elsevier, vol. 67(C), pages 1-15.
    10. 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.
    11. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    12. Peter N. Ireland, 2004. "Technology Shocks in the New Keynesian Model," The Review of Economics and Statistics, MIT Press, vol. 86(4), pages 923-936, November.
    13. Wolters, Maik H., 2011. "Forecasting under Model Uncertainty," VfS Annual Conference 2011 (Frankfurt, Main): The Order of the World Economy - Lessons from the Crisis 48723, Verein für Socialpolitik / German Economic Association.
    14. Jean-Philippe Cayen & Marc-André Gosselin & Sharon Kozicki, 2009. "Estimating DSGE-Model-Consistent Trends for Use in Forecasting," Staff Working Papers 09-35, Bank of Canada.
    15. Dr. James Mitchell, 2005. "Evaluating, comparing and combining density forecasts using the KLIC with an application to the Bank of England and NIESR ÔfanÕ charts of inflation," National Institute of Economic and Social Research (NIESR) Discussion Papers 253, National Institute of Economic and Social Research.
    16. Gerke, R. & Jonsson, M. & Kliem, M. & Kolasa, M. & Lafourcade, P. & Locarno, A. & Makarski, K. & McAdam, P., 2013. "Assessing macro-financial linkages: A model comparison exercise," Economic Modelling, Elsevier, vol. 31(C), pages 253-264.
    17. Bernanke, Ben S. & Gertler, Mark & Gilchrist, Simon, 1999. "The financial accelerator in a quantitative business cycle framework," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 21, pages 1341-1393, Elsevier.
    18. Diebold, Francis X & Gunther, Todd A & Tay, Anthony S, 1998. "Evaluating Density Forecasts with Applications to Financial Risk Management," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 863-883, November.
    19. Canzoneri, Matthew B. & Cumby, Robert E. & Diba, Behzad T., 2007. "Euler equations and money market interest rates: A challenge for monetary policy models," Journal of Monetary Economics, Elsevier, vol. 54(7), pages 1863-1881, October.
    20. Herbst, Edward & Schorfheide, Frank, 2012. "Evaluating DSGE model forecasts of comovements," Journal of Econometrics, Elsevier, vol. 171(2), pages 152-166.
    21. Amisano, Gianni & Giacomini, Raffaella, 2007. "Comparing Density Forecasts via Weighted Likelihood Ratio Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 177-190, April.
    22. Timmermann, Allan, 2006. "Forecast Combinations," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 4, pages 135-196, Elsevier.
    23. Del Negro, Marco & Schorfheide, Frank & Smets, Frank & Wouters, Rafael, 2007. "On the Fit of New Keynesian Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 123-143, April.
    24. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 2005. "Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 1-45, February.
    25. Geweke, John & Amisano, Gianni, 2011. "Optimal prediction pools," Journal of Econometrics, Elsevier, vol. 164(1), pages 130-141, September.
    26. Capistrán, Carlos & Timmermann, Allan, 2009. "Forecast Combination With Entry and Exit of Experts," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 428-440.
    27. 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.
    28. Andrea Gerali & Stefano Neri & Luca Sessa & Federico M. Signoretti, 2010. "Credit and Banking in a DSGE Model of the Euro Area," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(s1), pages 107-141, September.
    29. James Mitchell & Stephen G. Hall, 2005. "Evaluating, Comparing and Combining Density Forecasts Using the KLIC with an Application to the Bank of England and NIESR ‘Fan’ Charts of Inflation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 995-1033, December.
    30. John Geweke & Gianni Amisano, 2014. "Analysis of Variance for Bayesian Inference," Econometric Reviews, Taylor & Francis Journals, vol. 33(1-4), pages 270-288, June.
    31. 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.
    32. Negro, Marco Del & Schorfheide, Frank, 2013. "DSGE Model-Based Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 57-140, Elsevier.
    33. 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.
    34. Roberto Motto & Massimo Rostagno & Lawrence J. Christiano, 2010. "Financial Factors in Economic Fluctuations," 2010 Meeting Papers 141, Society for Economic Dynamics.
    35. G. Elliott & C. Granger & A. Timmermann (ed.), 2013. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 2, number 2.
    36. James Mitchell & Kenneth F. Wallis, 2011. "Evaluating density forecasts: forecast combinations, model mixtures, calibration and sharpness," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(6), pages 1023-1040, September.
    37. Rochelle M. Edge & Refet S. Gurkaynak, 2010. "How Useful Are Estimated DSGE Model Forecasts for Central Bankers?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 41(2 (Fall)), pages 209-259.
    38. Dr. James Mitchell, 2005. "Evaluating, comparing and combining density forecasts using the KLIC with an application to the Bank of England and NIESR ÔfanÕ charts of inflation," National Institute of Economic and Social Research (NIESR) Discussion Papers 253, National Institute of Economic and Social Research.
    39. Brzoza-Brzezina, Michał & Kolasa, Marcin & Makarski, Krzysztof, 2013. "The anatomy of standard DSGE models with financial frictions," Journal of Economic Dynamics and Control, Elsevier, vol. 37(1), pages 32-51.
    40. G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1.
    41. 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.
    42. Frank Smets & Raf Wouters, 2003. "An Estimated Dynamic Stochastic General Equilibrium Model of the Euro Area," Journal of the European Economic Association, MIT Press, vol. 1(5), pages 1123-1175, September.
    Full references (including those not matched with items on IDEAS)

    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. Negro, Marco Del & Schorfheide, Frank, 2013. "DSGE Model-Based Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 57-140, Elsevier.
    2. Hasumi, Ryo & Iiboshi, Hirokuni & Matsumae, Tatsuyoshi & Nakamura, Daisuke, 2019. "Does a financial accelerator improve forecasts during financial crises? Evidence from Japan with prediction-pooling methods," Journal of Asian Economics, Elsevier, vol. 60(C), pages 45-68.
    3. McAdam, Peter & Warne, Anders, 2019. "Euro area real-time density forecasting with financial or labor market frictions," International Journal of Forecasting, Elsevier, vol. 35(2), pages 580-600.
    4. 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.
    5. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    6. Lindé, Jesper & Smets, Frank & Wouters, Rafael, 2016. "Challenges for Central Banks´ Macro Models," Working Paper Series 323, Sveriges Riksbank (Central Bank of Sweden).
    7. 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.
    8. Chauvet, Marcelle & Potter, Simon, 2013. "Forecasting Output," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 141-194, Elsevier.
    9. Hasumi, Ryo & Iiboshi, Hirokuni & Matsumae, Tatsuyoshi & Nakamura, Daisuke, 2018. "Does a financial accelerator improve forecasts during financial crises?: Evidence from Japan with Prediction Pool Methods," MPRA Paper 85523, University Library of Munich, Germany.
    10. Michał Brzoza‐Brzezina & Marcin Kolasa, 2013. "Bayesian Evaluation of DSGE Models with Financial Frictions," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(8), pages 1451-1476, December.
    11. Cardani, Roberta & Paccagnini, Alessia & Villa, Stefania, 2019. "Forecasting with instabilities: An application to DSGE models with financial frictions," Journal of Macroeconomics, Elsevier, vol. 61(C), pages 1-1.
    12. Čapek, Jan & Crespo Cuaresma, Jesús & Hauzenberger, Niko & Reichel, Vlastimil, 2023. "Macroeconomic forecasting in the euro area using predictive combinations of DSGE models," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1820-1838.
    13. Anders Warne & Günter Coenen & Kai Christoffel, 2017. "Marginalized Predictive Likelihood Comparisons of Linear Gaussian State‐Space Models with Applications to DSGE, DSGE‐VAR, and VAR Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 103-119, January.
    14. Cai, Michael & Del Negro, Marco & Giannoni, Marc P. & Gupta, Abhi & Li, Pearl & Moszkowski, Erica, 2019. "DSGE forecasts of the lost recovery," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1770-1789.
    15. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2010. "Forecasting with DSGE models," Working Paper Series 1185, European Central Bank.
    16. Lindé, J. & Smets, F. & Wouters, R., 2016. "Challenges for Central Banks’ Macro Models," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 2185-2262, Elsevier.
    17. Nalban, Valeriu, 2018. "Forecasting with DSGE models: What frictions are important?," Economic Modelling, Elsevier, vol. 68(C), pages 190-204.
    18. Andrew Martinez, 2017. "Testing for Differences in Path Forecast Accuracy: Forecast-Error Dynamics Matter," Working Papers (Old Series) 1717, Federal Reserve Bank of Cleveland.
    19. Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2015. "Forecasting in a DSGE Model with Banking Intermediation: Evidence from the US," Working Papers 292, University of Milano-Bicocca, Department of Economics, revised Feb 2015.
    20. Michael Cai & Marco Del Negro & Edward Herbst & Ethan Matlin & Reca Sarfati & Frank Schorfheide, 2021. "Online estimation of DSGE models," The Econometrics Journal, Royal Economic Society, vol. 24(1), pages 33-58.

    More about this item

    Keywords

    Forecasting; DSGE models; Financial frictions; Housing market;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

    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:eee:intfor:v:31:y:2015:i:1:p:1-19. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijforecast .

    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.