IDEAS home Printed from https://ideas.repec.org/p/mnb/wpaper/2009-1.html
   My bibliography  Save this paper

A joint macroeconomic-yield curve model for Hungary

Author

Listed:
  • Zoltán Reppa

    (Magyar Nemzeti Bank)

Abstract

The main goal of this paper is to examine the relationship between macroeconomic shocks and yield curve movements in Hungary. To this end, we apply a Nelson-Siegel type dynamic yield curve model, where changes of the yield curve are driven by two latent factors and some key macro variables that follow a VAR(1) process. The structural macroeconomic shocks are identified by sign restrictions. According to the model, more than sixty percent of the variation of the yield curve factors can be explained by macro shocks. In particular, the monetary policy shock is the most important determinant of the level factor, while the slope factor is mainly driven by risk premium and demand shocks. As for the direction of the responses, monetary policy and supply shocks decrease long forward rates, while premium and demand shocks increase short forward rates. The effect of the premium and monetary policy shocks is strongest in the period when the shock occurs, while for the demand and supply shocks the responses reach their peak only after some delay.

Suggested Citation

  • Zoltán Reppa, 2009. "A joint macroeconomic-yield curve model for Hungary," MNB Working Papers 2009/1, Magyar Nemzeti Bank (Central Bank of Hungary).
  • Handle: RePEc:mnb:wpaper:2009/1
    as

    Download full text from publisher

    File URL: http://www.mnb.hu/letoltes/wp-2009-1.pdf
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Jin, Xisong & Nadal De Simone, Francisco, 2020. "Monetary policy and systemic risk-taking in the Euro area investment fund industry: A structural factor-augmented vector autoregression analysis," Journal of Financial Stability, Elsevier, vol. 49(C).
    2. Kabundi, Alain & De Simone, Francisco Nadal, 2022. "Euro area banking and monetary policy shocks in the QE era," Journal of Financial Stability, Elsevier, vol. 63(C).
    3. K. Istrefi & A. Piloiu, 2016. "Economic policy uncertainty and inflation expectations," Rue de la Banque, Banque de France, issue 33, november..
    4. Gábor Pellényi, 2012. "The Sectoral Effects of Monetary Policy in Hungary: A Structural Factor Analysis," MNB Working Papers 2012/1, Magyar Nemzeti Bank (Central Bank of Hungary).
    5. Pellényi, Gábor, 2012. "A monetáris politika hatása a magyar gazdaságra. Elemzés strukturális, dinamikus faktormodellel [The sectoral effects of monetary policy in Hungary: a structural factor]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(3), pages 263-284.
    6. Kabundi, Alain & De Simone, Francisco Nadal, 2020. "Monetary policy and systemic risk-taking in the euro area banking sector," Economic Modelling, Elsevier, vol. 91(C), pages 736-758.
    7. Paredes, Joan, 2017. "Subsidising car purchases in the euro area: any spill-over on production?," Working Paper Series 2094, European Central Bank.
    8. Bálint Tamási & Balázs Világi, 2011. "Identification of credit supply shocks in a Bayesian SVAR model of the Hungarian economy," MNB Working Papers 2011/7, Magyar Nemzeti Bank (Central Bank of Hungary).
    9. Martina Makarieva, 2021. "Yield curve modelling and forecasting in an undeveloped financial market: The case of Bulgaria," Economic Thought journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 2, pages 61-83,84-10.
    10. Boril Šopov & Jakub Seidler, 2011. "Yield Curve Dynamics: Regional Common Factor Model," Prague Economic Papers, Prague University of Economics and Business, vol. 2011(2), pages 140-156.

    More about this item

    Keywords

    yield curve; Nelson-Siegel; factor models; state space models; structural identification.;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:mnb:wpaper:2009/1. 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.

    We have no bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Lorant Kaszab (email available below). General contact details of provider: https://edirc.repec.org/data/mnbgvhu.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.