IDEAS home Printed from https://ideas.repec.org/p/ptu/wpaper/w199904.html
   My bibliography  Save this paper

Simulated Likelihood Estimation of Non-Linear Diffusion Processes Through Non-Parametric Procedure With an Application to the Portuguese Interest Rate

Author

Listed:
  • João Nicolau

Abstract

In this article we present a new model of the spot interest rate and a new method of estimation of nonlinear stochastic differential equations. We show how an integrated discrete time process in an econometric sense can be modelled by a continuous time ergodic process. We make an application to the Portuguese spot interest rate.

Suggested Citation

  • João Nicolau, 1999. "Simulated Likelihood Estimation of Non-Linear Diffusion Processes Through Non-Parametric Procedure With an Application to the Portuguese Interest Rate," Working Papers w199904, Banco de Portugal, Economics and Research Department.
  • Handle: RePEc:ptu:wpaper:w199904
    as

    Download full text from publisher

    File URL: https://www.bportugal.pt/sites/default/files/anexos/papers/wp199904.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Fuhrer, Jeffrey C, 1997. "The (Un)Importance of Forward-Looking Behavior in Price Specifications," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 29(3), pages 338-350, August.
    2. Taylor, John B, 1980. "Aggregate Dynamics and Staggered Contracts," Journal of Political Economy, University of Chicago Press, vol. 88(1), pages 1-23, February.
    3. Jose Manuel Campa & Linda S. Goldberg, 2002. "Exchange Rate Pass-Through into Import Prices: A Macro or Micro Phenomenon?," NBER Working Papers 8934, National Bureau of Economic Research, Inc.
    4. Coenen, Gunter & Wieland, Volker, 2005. "A small estimated euro area model with rational expectations and nominal rigidities," European Economic Review, Elsevier, vol. 49(5), pages 1081-1104, July.
    5. Bankim Chadha & Paul R. Masson & Guy Meredith, 1992. "Models of Inflation and the Costs of Disinflation," IMF Staff Papers, Palgrave Macmillan, vol. 39(2), pages 395-431, June.
    6. Prachowny, Martin F J, 1993. "Okun's Law: Theoretical Foundations and Revised Estimates," The Review of Economics and Statistics, MIT Press, vol. 75(2), pages 331-336, May.
    7. Zivot, Eric & Andrews, Donald W K, 2002. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 25-44, January.
    8. Newey, Whitney K & West, Kenneth D, 1987. "Hypothesis Testing with Efficient Method of Moments Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 28(3), pages 777-787, October.
    9. Clarida, Richard & Gali, Jordi & Gertler, Mark, 1998. "Monetary policy rules in practice Some international evidence," European Economic Review, Elsevier, vol. 42(6), pages 1033-1067, June.
    10. Gert Schnabel, 2002. "Output trends and Okun's law," BIS Working Papers 111, Bank for International Settlements.
    11. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    12. McCallum, Bennett T & Nelson, Edward, 1999. "An Optimizing IS-LM Specification for Monetary Policy and Business Cycle Analysis," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 31(3), pages 296-316, August.
    13. Ramdane Djoudad & Céline Gauthier, 2003. "A Small Dynamic Hybrid Model for the Euro Area," Staff Working Papers 03-19, Bank of Canada.
    14. Brand, Claus & Cassola, Nuno, 2000. "A money demand system for euro area M3," Working Paper Series 0039, European Central Bank.
    15. Attfield, Clifford L. F. & Silverstone, Brian, 1998. "Okun's Law, Cointegration and Gap Variables," Journal of Macroeconomics, Elsevier, vol. 20(3), pages 625-637, July.
    16. Clifford L. F. Attfield & Brian Silverstone, 1997. "Okun's Coefficient: A Comment," The Review of Economics and Statistics, MIT Press, vol. 79(2), pages 326-329, May.
    17. Taylor, John B., 1999. "The robustness and efficiency of monetary policy rules as guidelines for interest rate setting by the European central bank," Journal of Monetary Economics, Elsevier, vol. 43(3), pages 655-679, June.
    18. Peersman, Gert & Smets, Frank, 2001. "The monetary transmission mechanism in the euro area: more evidence from VAR analysis," Working Paper Series 0091, European Central Bank.
    19. Richard H. Clarida & Jordi Gali & Mark Gertler, 1998. "Monetary policy rules in practice," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.
    20. Gerdesmeier, Dieter & Roffia, Barbara, 2003. "Empirical estimates of reaction functions for the euro area," Working Paper Series 206, European Central Bank.
    21. Juillard, Michel & Laxton, Douglas & McAdam, Peter & Pioro, Hope, 1998. "An algorithm competition: First-order iterations versus Newton-based techniques," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1291-1318, August.
    22. 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.
    23. Jeff Fuhrer & George Moore, 1995. "Inflation Persistence," The Quarterly Journal of Economics, Oxford University Press, vol. 110(1), pages 127-159.
    Full references (including those not matched with items on IDEAS)

    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

    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:ptu:wpaper:w199904. 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: (DEE-NTDD). General contact details of provider: http://edirc.repec.org/data/bdpgvpt.html .

    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.

    We have no references for this item. You can help adding them by using 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.