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A Dynamic Yield Curve Model with Stochastic Volatility and Non-Gaussian Interactions: An Empirical Study of Non-standard Monetary Policy in the Euro Area

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  • Geert Mesters

    (VU University Amsterdam, the Netherlands)

  • Bernd Schwaab

    (European Central Bank)

  • Siem Jan Koopman

    (VU University Amsterdam, the Netherlands)

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    Abstract

    We develop an econometric methodology for the study of the yield curve and its interactions with measures of non-standard monetary policy during possibly turbulent times. The yield curve is modeled by the dynamic Nelson-Siegel model while the monetary policy measurements are modeled as non-Gaussian variables that interact with latent dynamic factors, including the yield factors of level and slope. Yield developments during the financial and sovereign debt crises require the yield curve model to be extended with stochastic volatility and heavy tailed disturbances. We develop a flexible estimation method for the model parameters with a novel implementation of the importance sampling technique. We empirically investigate how the yields in Germany, France, Italy and Spain have been affected by monetary policy measures of the European Central Bank. We model the euro area interbank lending rate EONIA by a log-normal distribution and the bond market purchases within the ECB's Securities Markets Programme by a Poisson distribution. We find evidence that the bond market interventions had a direct and temporary effect on the yield curve lasting up to ten weeks, and find limited evidence that purchases changed the relationship between the EONIA rate and the term structure factors.

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    Bibliographic Info

    Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 14-071/III.

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    Date of creation: 17 Jun 2014
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    Handle: RePEc:dgr:uvatin:20140071

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    Web page: http://www.tinbergen.nl

    Related research

    Keywords: dynamic Nelson-Siegel models; Central bank asset purchases; non-Gaussian; state space methods; importance sampling; European Central Bank;

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    1. Dewachter, H.D.R. & Lyrio, M., 2003. "Macro factors and the Term Structure of Interest Rates," ERIM Report Series Research in Management, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasm ERS-2003-037-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    2. D'Amico, Stefania & English, William & López-Salido, J David & Nelson, Edward, 2012. "The Federal Reserve’s Large-Scale Asset Purchase Programs: Rationale and Effects," CEPR Discussion Papers, C.E.P.R. Discussion Papers 9145, C.E.P.R. Discussion Papers.
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    4. Tsunehiro Ishihara & Yasuhiro Omori, 2009. "Multivariate Stochastic Volatility with Cross Leverage," CIRJE F-Series CIRJE-F-690, CIRJE, Faculty of Economics, University of Tokyo.
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    7. Manabu Asai & Massimiliano Caporin & Michael McAleer, 2009. "Block Structure Multivariate Stochastic Volatility Models," CIRJE F-Series CIRJE-F-699, CIRJE, Faculty of Economics, University of Tokyo.
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    9. Koopman, Siem Jan & Mallee, Max I. P. & Van der Wel, Michel, 2010. "Analyzing the Term Structure of Interest Rates Using the Dynamic Nelson–Siegel Model With Time-Varying Parameters," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 28(3), pages 329-343.
    10. Eser, Fabian & Carmona Amaro, Marta & Iacobelli, Stefano & Rubens, Marc, 2012. "The use of the Eurosystem's monetary policy instruments and operational framework since 2009," Occasional Paper Series 135, European Central Bank.
    11. Francis X. Diebold & Glenn D. Rudebusch, 2012. "Yield Curve Modeling and Forecasting: The Dynamic Nelson-Siegel Approach," Economics Books, Princeton University Press, edition 1, volume 1, number 9895.
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    13. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods: Second Edition," OUP Catalogue, Oxford University Press, Oxford University Press, number 9780199641178, October.
    14. J. Durbin, 2002. "A simple and efficient simulation smoother for state space time series analysis," Biometrika, Biometrika Trust, Biometrika Trust, vol. 89(3), pages 603-616, August.
    15. Stefania D'Amico & Thomas B. King, 2012. "Flow and stock effects of large-scale asset purchases: evidence on the importance of local supply," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.) 2012-44, Board of Governors of the Federal Reserve System (U.S.).
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