IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v133y2015icp89-91.html
   My bibliography  Save this article

Solving and estimating linearized DSGE models with VARMA shock processes and filtered data

Author

Listed:
  • Meyer-Gohde, Alexander
  • Neuhoff, Daniel

Abstract

We derive recursive solutions to linearized DSGE models with VARMA exogenous driving forces of arbitrary order without inflating the state vector. Representing the solution in the frequency domain, we calculate the likelihood of a sequence of observations from the model, as well as its nonrecursively filtered (e.g., Hodrick–Prescott or Baxter–King) variant straightforwardly.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ecolet:v:133:y:2015:i:c:p:89-91
    DOI: 10.1016/j.econlet.2015.05.024
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176515002190
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econlet.2015.05.024?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Klein, Paul, 2000. "Using the generalized Schur form to solve a multivariate linear rational expectations model," Journal of Economic Dynamics and Control, Elsevier, vol. 24(10), pages 1405-1423, September.
    2. 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.
    3. Massimiliano Croce, Mariano, 2014. "Long-run productivity risk: A new hope for production-based asset pricing?," Journal of Monetary Economics, Elsevier, vol. 66(C), pages 13-31.
    4. Marianne Baxter & Robert G. King, 1999. "Measuring Business Cycles: Approximate Band-Pass Filters For Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 575-593, November.
    5. 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.
    6. Ricardo Reis & Vasco Curdia, 2009. "Correlated Disturbances and U.S. Business Cycles," 2009 Meeting Papers 129, Society for Economic Dynamics.
    7. Hodrick, Robert J & Prescott, Edward C, 1997. "Postwar U.S. Business Cycles: An Empirical Investigation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(1), pages 1-16, February.
    8. King, Robert G. & Rebelo, Sergio T., 1993. "Low frequency filtering and real business cycles," Journal of Economic Dynamics and Control, Elsevier, vol. 17(1-2), pages 207-231.
    9. Lan, Hong & Meyer-Gohde, Alexander, 2014. "Solvability of perturbation solutions in DSGE models," Journal of Economic Dynamics and Control, Elsevier, vol. 45(C), pages 366-388.
    10. Anderson, Gary S., 2010. "A reliable and computationally efficient algorithm for imposing the saddle point property in dynamic models," Journal of Economic Dynamics and Control, Elsevier, vol. 34(3), pages 472-489, March.
    11. Meyer-Gohde, Alexander, 2010. "Linear rational-expectations models with lagged expectations: A synthetic method," Journal of Economic Dynamics and Control, Elsevier, vol. 34(5), pages 984-1002, May.
    12. Schmitt-Grohé, Stephanie & Uribe, Martín, 2010. "Evaluating the sample likelihood of linearized DSGE models without the use of the Kalman filter," Economics Letters, Elsevier, vol. 109(3), pages 142-143, December.
    13. Marimon, Ramon & Scott, Andrew (ed.), 1999. "Computational Methods for the Study of Dynamic Economies," OUP Catalogue, Oxford University Press, number 9780198294979, Decembrie.
    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. Meyer-Gohde, Alexander & Neuhoff, Daniel, 2015. "Generalized exogenous processes in DSGE: A Bayesian approach," SFB 649 Discussion Papers 2015-014, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    2. Meyer-Gohde, Alexander, 2024. "Solving and analyzing DSGE models in the frequency domain," IMFS Working Paper Series 207, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
    3. Morris, Stephen D., 2016. "VARMA representation of DSGE models," Economics Letters, Elsevier, vol. 138(C), pages 30-33.

    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. Meyer-Gohde, Alexander & Neuhoff, Daniel, 2015. "Generalized exogenous processes in DSGE: A Bayesian approach," SFB 649 Discussion Papers 2015-014, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    2. repec:hum:wpaper:sfb649dp2015-014 is not listed on IDEAS
    3. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2010. "Forecasting with DSGE models," Working Paper Series 1185, European Central Bank.
    4. 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.
    5. Adrien Auclert & Bence Bardóczy & Matthew Rognlie & Ludwig Straub, 2021. "Using the Sequence‐Space Jacobian to Solve and Estimate Heterogeneous‐Agent Models," Econometrica, Econometric Society, vol. 89(5), pages 2375-2408, September.
    6. Lan, Hong & Meyer-Gohde, Alexander, 2013. "Solving DSGE models with a nonlinear moving average," Journal of Economic Dynamics and Control, Elsevier, vol. 37(12), pages 2643-2667.
    7. Hansen, G.D. & Ohanian, L.E., 2016. "Neoclassical Models in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 2043-2130, Elsevier.
    8. Mertens, Elmar, 2010. "Structural shocks and the comovements between output and interest rates," Journal of Economic Dynamics and Control, Elsevier, vol. 34(6), pages 1171-1186, June.
    9. Andrea Tambalotti & Andrea Ferrero & Vasco Curdia, 2010. "Evaluating Interest Rate Rules in an Estimated DSGE Model," 2010 Meeting Papers 402, Society for Economic Dynamics.
    10. 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.
    11. Fernández-Villaverde, J. & Rubio-Ramírez, J.F. & Schorfheide, F., 2016. "Solution and Estimation Methods for DSGE Models," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 527-724, Elsevier.
    12. Lars-H. R. Siemers, 2024. "On the Hamilton-HP Filter Controversy: Evidence from German Business Cycles," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 20(3), pages 367-409, November.
    13. Prabheesh, K.P. & Anglingkusumo, Reza & Juhro, Solikin M., 2021. "The dynamics of global financial cycle and domestic economic cycles: Evidence from India and Indonesia," Economic Modelling, Elsevier, vol. 94(C), pages 831-842.
    14. Maravall, A. & del Rio, A., 2007. "Temporal aggregation, systematic sampling, and the Hodrick-Prescott filter," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 975-998, October.
    15. Hall, Viv B & Thomson, Peter, 2022. "A boosted HP filter for business cycle analysis: evidence from New Zealand’s small open economy," Working Paper Series 9473, Victoria University of Wellington, School of Economics and Finance.
    16. Ibrahim Ahamada & Philippe Jolivaldt, 2010. "Filtres usuels et filtre fondé sur les ondelettes : étude comparative et application au cycle économique," Economie & Prévision, La Documentation Française, vol. 0(4), pages 149-161.
    17. Barrales-Ruiz, Jose & Arnim, Rudiger von, 2021. "Endogenous fluctuations in demand and distribution: An empirical investigation," Structural Change and Economic Dynamics, Elsevier, vol. 58(C), pages 204-220.
    18. Lubik, Thomas A. & Matthes, Christian & Verona, Fabio, 2019. "Assessing U.S. aggregate fluctuations across time and frequencies," Bank of Finland Research Discussion Papers 5/2019, Bank of Finland.
    19. Andrew Foerster & Juan F. Rubio‐Ramírez & Daniel F. Waggoner & Tao Zha, 2016. "Perturbation methods for Markov‐switching dynamic stochastic general equilibrium models," Quantitative Economics, Econometric Society, vol. 7(2), pages 637-669, July.
    20. 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.
    21. Tripier, Fabien, 2006. "Sticky prices, fair wages, and the co-movements of unemployment and labor productivity growth," Journal of Economic Dynamics and Control, Elsevier, vol. 30(12), pages 2749-2774, December.

    More about this item

    Keywords

    DSGE models; ARMA; VAR; Likelihood function;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications

    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:ecolet:v:133:y:2015:i:c:p:89-91. 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/ecolet .

    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.