IDEAS home Printed from https://ideas.repec.org/p/red/sed009/129.html
   My bibliography  Save this paper

Correlated Disturbances and U.S. Business Cycles

Author

Listed:
  • Ricardo Reis

    (Columbia University)

  • Vasco Curdia

    (FRB New York)

Abstract

The dynamic stochastic general equilibrium (DSGE) models used to study business cycles typically assume that exogenous disturbances are independent with a simple structure for serial correlation. This paper relaxes this tight restriction, by allowing for disturbances that have a rich contemporaneous and dynamic correlation structure. Our first contribution is a new Bayesian econometric method that uses conjugate conditionals to make the estimation of DSGE models with correlated disturbances feasible and quick. Our second contribution is a re-examination of the sources of U.S. business cycles, using two canonical models, one real and the other monetary. We find that when we allow for correlated disturbances, the estimates of crucial parameters are more in line with other evidence, the impulse responses are closer to the results from vector autoregressions, and government spending and technology disturbances play a larger role in the business cycle, while changes in markups are unimportant

Suggested Citation

  • Ricardo Reis & Vasco Curdia, 2009. "Correlated Disturbances and U.S. Business Cycles," 2009 Meeting Papers 129, Society for Economic Dynamics.
    • Handle: RePEc:red:sed009:129
    as

    Download full text from publisher

    File URL: https://red-files-public.s3.amazonaws.com/meetpapers/2009/paper_129.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Geweke, John, 1989. "Bayesian Inference in Econometric Models Using Monte Carlo Integration," Econometrica, Econometric Society, vol. 57(6), pages 1317-1339, November.
    2. Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez, 2007. "Estimating Macroeconomic Models: A Likelihood Approach," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 74(4), pages 1059-1087.
    3. Motohiro Yogo, 2004. "Estimating the Elasticity of Intertemporal Substitution When Instruments Are Weak," The Review of Economics and Statistics, MIT Press, vol. 86(3), pages 797-810, August.
    4. Chib, Siddhartha, 2001. "Markov chain Monte Carlo methods: computation and inference," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 57, pages 3569-3649, Elsevier.
    5. 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.
    6. James H. Stock, 2010. "The Other Transformation in Econometric Practice: Robust Tools for Inference," Journal of Economic Perspectives, American Economic Association, vol. 24(2), pages 83-94, Spring.
    7. Cogley, Timothy & Nason, James M, 1995. "Output Dynamics in Real-Business-Cycle Models," American Economic Review, American Economic Association, vol. 85(3), pages 492-511, June.
    8. V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2009. "New Keynesian Models: Not Yet Useful for Policy Analysis," American Economic Journal: Macroeconomics, American Economic Association, vol. 1(1), pages 242-266, January.
    9. Jonas D. M. Fisher, 2006. "The Dynamic Effects of Neutral and Investment-Specific Technology Shocks," Journal of Political Economy, University of Chicago Press, vol. 114(3), pages 413-451, June.
    10. Hall, Robert E, 1997. "Macroeconomic Fluctuations and the Allocation of Time," Journal of Labor Economics, University of Chicago Press, vol. 15(1), pages 223-250, January.
    11. Parkin, Michael, 1988. "A method for determining whether parameters in aggregative models are structural," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 29(1), pages 215-252, January.
    12. Lubik, Thomas A. & Schorfheide, Frank, 2007. "Do central banks respond to exchange rate movements? A structural investigation," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1069-1087, May.
    13. 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.
    14. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178.
    15. Francis, Neville & Ramey, Valerie A., 2005. "Is the technology-driven real business cycle hypothesis dead? Shocks and aggregate fluctuations revisited," Journal of Monetary Economics, Elsevier, vol. 52(8), pages 1379-1399, November.
    16. Christiano, Lawrence J & Eichenbaum, Martin, 1992. "Current Real-Business-Cycle Theories and Aggregate Labor-Market Fluctuations," American Economic Review, American Economic Association, vol. 82(3), pages 430-450, June.
    17. Evans, Charles L., 1992. "Productivity shocks and real business cycles," Journal of Monetary Economics, Elsevier, vol. 29(2), pages 191-208, April.
    18. V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2007. "Business Cycle Accounting," Econometrica, Econometric Society, vol. 75(3), pages 781-836, May.
    19. Justiniano, Alejandro & Preston, Bruce, 2010. "Can structural small open-economy models account for the influence of foreign disturbances?," Journal of International Economics, Elsevier, vol. 81(1), pages 61-74, May.
    20. Hall, Robert E, 1988. "Intertemporal Substitution in Consumption," Journal of Political Economy, University of Chicago Press, vol. 96(2), pages 339-357, April.
    21. Ralph S.J. Koijen & Jules H. van Binsbergen & Juan F. Rubio-Ramírez & Jesus Fernandez-Villaverde, 2008. "Likelihood Estimation of DSGE Models with Epstein-Zin Preferences," 2008 Meeting Papers 1099, Society for Economic Dynamics.
    22. Dedola, Luca & Neri, Stefano, 2007. "What does a technology shock do? A VAR analysis with model-based sign restrictions," Journal of Monetary Economics, Elsevier, vol. 54(2), pages 512-549, March.
    23. Stephanie Schmitt-Grohe & Martin Uribe, 2011. "Business Cycles With A Common Trend in Neutral and Investment-Specific Productivity," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 14(1), pages 122-135, January.
    24. Chib, Siddhartha & Ramamurthy, Srikanth, 2010. "Tailored randomized block MCMC methods with application to DSGE models," Journal of Econometrics, Elsevier, vol. 155(1), pages 19-38, March.
    25. 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 949-968, November.
    26. Yongsung Chang & Sun-Bin Kim, 2007. "Heterogeneity and Aggregation: Implications for Labor-Market Fluctuations," American Economic Review, American Economic Association, vol. 97(5), pages 1939-1956, December.
    27. 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.
    28. Rabanal, Pau & Rubio-Ramírez, Juan F. & Tuesta, Vicente, 2011. "Cointegrated TFP processes and international business cycles," Journal of Monetary Economics, Elsevier, vol. 58(2), pages 156-171, March.
    29. Greenwood, Jeremy & Hercowitz, Zvi & Krusell, Per, 1997. "Long-Run Implications of Investment-Specific Technological Change," American Economic Review, American Economic Association, vol. 87(3), pages 342-362, June.
    30. 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.
    31. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    32. Sargent, Thomas J, 1978. "Estimation of Dynamic Labor Demand Schedules under Rational Expectations," Journal of Political Economy, University of Chicago Press, vol. 86(6), pages 1009-1044, December.
    33. 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.
    34. Ricardo Reis, 2007. "Using VARs to Identify Models of Fiscal Policy: A Comment on Perotti," Working Papers 1044, Princeton University, Woodrow Wilson School of Public and International Affairs, Discussion Papers in Economics.
    35. Dedola, Luca & Neri, Stefano, 2007. "What does a technology shock do? A VAR analysis with model-based sign restrictions," Journal of Monetary Economics, Elsevier, vol. 54(2), pages 512-549, March.
    36. 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)

    Citations

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


    Cited by:

    1. Giovanni Angelini & Luca Fanelli, 2016. "Misspecification and Expectations Correction in New Keynesian DSGE Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(5), pages 623-649, October.
    2. Saroj Bhattarai & Jae Won Lee & Woong Yong Park, 2016. "Policy Regimes, Policy Shifts, and U.S. Business Cycles," The Review of Economics and Statistics, MIT Press, vol. 98(5), pages 968-983, December.
    3. Inoue, Atsushi & Kuo, Chun-Hung & Rossi, Barbara, 2020. "Identifying the sources of model misspecification," Journal of Monetary Economics, Elsevier, vol. 110(C), pages 1-18.
    4. Pinter, Gabor, 2018. "Macroeconomic shocks and risk premia," LSE Research Online Documents on Economics 90370, London School of Economics and Political Science, LSE Library.
    5. Bask, Mikael & Madeira, João, 2011. "The Increased Importance of Asset Price Misalignments for Business Cycle Dynamics," Working Paper Series 2011:12, Uppsala University, Department of Economics.
    6. Mehkari, M. Saif, 2016. "Uncertainty shocks in a model with mean-variance frontiers and endogenous technology choices," Journal of Macroeconomics, Elsevier, vol. 49(C), pages 71-98.
    7. Monti, Francesca, 2015. "Can a data-rich environment help identify the sources of model misspecification?," LSE Research Online Documents on Economics 86320, London School of Economics and Political Science, LSE Library.
    8. Fabio Milani, 2011. "Expectation Shocks and Learning as Drivers of the Business Cycle," Economic Journal, Royal Economic Society, vol. 121(552), pages 379-401, May.
    9. 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.
    10. Patrick Fève & Jean-Guillaume Sahuc, 2015. "On the size of the government spending multiplier in the euro area," Oxford Economic Papers, Oxford University Press, vol. 67(3), pages 531-552.
    11. Pablo A. Guerrón-Quintana & James M. Nason, 2013. "Bayesian estimation of DSGE models," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 21, pages 486-512, Edward Elgar Publishing.
    12. Faust, Jon & Gupta, Abhishek, 2010. "Posterior Predictive Analysis for Evaluating DSGE Models," MPRA Paper 26721, University Library of Munich, Germany.
    13. Madeira, João & Palma, Nuno, 2018. "Measuring monetary policy deviations from the Taylor rule," Economics Letters, Elsevier, vol. 168(C), pages 25-27.
    14. István Kónya, 2011. "Convergence and Distortions: the Czech Republic, Hungary and Poland between 1996–2009," MNB Working Papers 2011/6, Magyar Nemzeti Bank (Central Bank of Hungary).
    15. Meyer-Gohde, Alexander & Neuhoff, Daniel, 2015. "Solving and estimating linearized DSGE models with VARMA shock processes and filtered data," Economics Letters, Elsevier, vol. 133(C), pages 89-91.
    16. Corbo, Vesna & Strid, Ingvar, 2020. "MAJA: A two-region DSGE model for Sweden and its main trading partners," Working Paper Series 391, Sveriges Riksbank (Central Bank of Sweden).
    17. Tan, Fei & Walker, Todd B., 2015. "Solving generalized multivariate linear rational expectations models," Journal of Economic Dynamics and Control, Elsevier, vol. 60(C), pages 95-111.
    18. Çekin, Semih Emre & Ivashchenko, Sergey & Gupta, Rangan & Lee, Chien-Chiang, 2024. "Real-time forecast of DSGE models with time-varying volatility in GARCH form," International Review of Financial Analysis, Elsevier, vol. 93(C).
    19. Nikolay Gospodinov & Damba Lkhagvasuren, 2014. "A Moment‐Matching Method For Approximating Vector Autoregressive Processes By Finite‐State Markov Chains," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(5), pages 843-859, August.
    20. Christoffel, Kai & Kilponen, Juha & Jaccard, Ivan, 2011. "Government bond risk premia and the cyclicality of fiscal policy," Working Paper Series 1411, European Central Bank.
    21. Bachmann, Rüdiger & Bayer, Christian, 2013. "‘Wait-and-See’ business cycles?," Journal of Monetary Economics, Elsevier, vol. 60(6), pages 704-719.
    22. Nikolaos Kokonas & Paulo Santos Monteiro, 2020. "The Ins and Outs of Unemployment in General Equilibrium," Discussion Papers 2014, Centre for Macroeconomics (CFM).
    23. Kónya, István, 2011. "Növekedés és felzárkózás Magyarországon, 1995-2009 [Growth and convergence in Hungary, 1995-2009]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(5), pages 393-411.
    24. Chollete, Loran & Ismailescu, Iuliana & Lu, Ching-Chih, 2014. "Dependence between Extreme Events in the Real and Financial Sectors," UiS Working Papers in Economics and Finance 2014/12, University of Stavanger.

    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. Andrei Polbin & Sergey Drobyshevsky, 2014. "Developing a Dynamic Stochastic Model of General Equilibrium for the Russian Economy," Research Paper Series, Gaidar Institute for Economic Policy, issue 166P, pages 156-156.
    2. Born, Benjamin & Peter, Alexandra & Pfeifer, Johannes, 2013. "Fiscal news and macroeconomic volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 37(12), pages 2582-2601.
    3. Ramey, V.A., 2016. "Macroeconomic Shocks and Their Propagation," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 71-162, Elsevier.
    4. Gubler, Matthias & Hertweck, Matthias S., 2013. "Commodity price shocks and the business cycle: Structural evidence for the U.S," Journal of International Money and Finance, Elsevier, vol. 37(C), pages 324-352.
    5. Alok Johri & Muhebullah Karimzada, 2021. "Learning efficiency shocks, knowledge capital and the business cycle: A Bayesian evaluation," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 54(3), pages 1314-1360, November.
    6. Canova, Fabio & Paustian, Matthias, 2011. "Business cycle measurement with some theory," Journal of Monetary Economics, Elsevier, vol. 58(4), pages 345-361.
    7. Andrés González & Sergio Ocampo & Diego Rodríguez & Norberto Rodríguez, 2012. "Asimetrías del empleo y el producto, una aproximación de equilibrio general," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, vol. 30(68), pages 218-272, June.
    8. Haroon Mumtaz & Francesco Zanetti, 2012. "Neutral Technology Shocks And The Dynamics Of Labor Input: Results From An Agnostic Identification," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(1), pages 235-254, February.
    9. Canova, Fabio & Michelacci, Claudio & López-Salido, J David, 2007. "The Labour Market Effects of Technology Shocks," CEPR Discussion Papers 6365, C.E.P.R. Discussion Papers.
    10. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute, revised 04 Sep 2014.
    11. Pablo Burriel & Jesús Fernández-Villaverde & Juan Rubio-Ramírez, 2010. "MEDEA: a DSGE model for the Spanish economy," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 1(1), pages 175-243, March.
    12. Zheng Liu & Daniel F. Waggoner & Tao Zha, 2009. "Sources of the Great Moderation: shocks, frictions, or monetary policy?," FRB Atlanta Working Paper 2009-03, Federal Reserve Bank of Atlanta.
    13. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2010. "Forecasting with DSGE models," Working Paper Series 1185, European Central Bank.
    14. 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.
    15. Cristiano Cantore & Miguel León-Ledesma & Peter McAdam & Alpo Willman, 2014. "Shocking Stuff: Technology, Hours, And Factor Substitution," Journal of the European Economic Association, European Economic Association, vol. 12(1), pages 108-128, February.
    16. Alexander Falter & Dennis Wesselbaum, 2018. "Correlated shocks in estimated DSGE models," Economics Bulletin, AccessEcon, vol. 38(4), pages 2026-2036.
    17. Justiniano, Alejandro & Primiceri, Giorgio E. & Tambalotti, Andrea, 2010. "Investment shocks and business cycles," Journal of Monetary Economics, Elsevier, vol. 57(2), pages 132-145, March.
    18. Paccagnini, Alessia, 2017. "Dealing with Misspecification in DSGE Models: A Survey," MPRA Paper 82914, University Library of Munich, Germany.
    19. Bachmann, Rüdiger & Zorn, Peter, 2020. "What drives aggregate investment? Evidence from German survey data," Journal of Economic Dynamics and Control, Elsevier, vol. 115(C).
    20. 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.

    More about this item

    JEL classification:

    • E1 - Macroeconomics and Monetary Economics - - General Aggregative Models
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles

    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:red:sed009:129. 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: Christian Zimmermann (email available below). General contact details of provider: https://edirc.repec.org/data/sedddea.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.