IDEAS home Printed from https://ideas.repec.org/p/sgh/kaewps/2018035.html
   My bibliography  Save this paper

The non-linear nature of country risk and its implications for DSGE models

Author

Listed:
  • Michal Brzoza-Brzezina
  • Jacek Kotlowski

Abstract

Country risk premia can substantially affect macroeconomic dynamics. We concentrate on one of their most important determinants - a country’s net foreign asset position and - in contrast to the existing research - investigate its nonlinear link to risk premia. The importance of this particular non-linearity is twofold. First, it allows to identify the NFA level above which the elasticity becomes much (possibly dangerously) higher. Second, such a non-linear relationship is a standard ingredient of DSGE models, but its proper calibration/ estimation is missing. Our estimation shows that indeed the link is highly nonlinear and helps to identify the NFA position where the non-linearity kicks in at approximately -70% to -75% of GDP. We also provide a proper calibration of the risk premium - NFA relationship which can be used in DSGE models and demonstrate that its slope matters significantly for economic dynamics in such a model.

Suggested Citation

  • Michal Brzoza-Brzezina & Jacek Kotlowski, 2018. "The non-linear nature of country risk and its implications for DSGE models," Working Papers 2018-035, Warsaw School of Economics, Collegium of Economic Analysis.
  • Handle: RePEc:sgh:kaewps:2018035
    as

    Download full text from publisher

    File URL: http://kolegia.sgh.waw.pl/pl/KAE/Documents/WorkingPapersKAE/WPKAE_2018_035.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Schmitt-Grohe, Stephanie & Uribe, Martin, 2003. "Closing small open economy models," Journal of International Economics, Elsevier, vol. 61(1), pages 163-185, October.
    2. González, Andrés & Teräsvirta, Timo & van Dijk, Dick & Yang, Yukai, 2005. "Panel Smooth Transition Regression Models," SSE/EFI Working Paper Series in Economics and Finance 604, Stockholm School of Economics, revised 11 Oct 2017.
    3. Javier Garcia-Cicco & Roberto Pancrazi & Martin Uribe, 2010. "Real Business Cycles in Emerging Countries?," American Economic Review, American Economic Association, vol. 100(5), pages 2510-2531, December.
    4. Ciocchini, Francisco & Durbin, Erik & Ng, David T. C., 2003. "Does corruption increase emerging market bond spreads?," Journal of Economics and Business, Elsevier, vol. 55(5-6), pages 503-528.
    5. Lane, Philip R. & Milesi-Ferretti, Gian Maria, 2001. "The external wealth of nations: measures of foreign assets and liabilities for industrial and developing countries," Journal of International Economics, Elsevier, vol. 55(2), pages 263-294, December.
    6. Warne, Anders & Coenen, Günter & Christoffel, Kai, 2008. "The new area-wide model of the euro area: a micro-founded open-economy model for forecasting and policy analysis," Working Paper Series 944, European Central Bank.
    7. Peter Benczur & Istvan Konya, 2016. "Interest Premium, Sudden Stop, and Adjustment in a Small Open Economy," Eastern European Economics, Taylor & Francis Journals, vol. 54(4), pages 271-295, July.
    8. Raf Wouters & Frank Smets, 2005. "Comparing shocks and frictions in US and euro area business cycles: a Bayesian DSGE Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(2), pages 161-183.
    9. Falk, A. & Becker, A. & Dohmen, T.J. & Enke, B. & Huffman, D. & Sunde, U., 2015. "The nature and predictive power of preferences: Global evidence," Research Memorandum 039, Maastricht University, Graduate School of Business and Economics (GSBE).
    10. Thomas Dohmen & Benjamin Enke & Armin Falk & David Huffman & Uwe Sunde, 2016. "Patience and the Wealth of Nations," Working Papers 2016-012, Human Capital and Economic Opportunity Working Group.
    11. Álvaro Escribano & Oscar Jordá, 2001. "Testing nonlinearity: Decision rules for selecting between logistic and exponential STAR models," Spanish Economic Review, Springer;Spanish Economic Association, vol. 3(3), pages 193-209.
    12. Hansen, Bruce E, 1996. "Inference When a Nuisance Parameter Is Not Identified under the Null Hypothesis," Econometrica, Econometric Society, vol. 64(2), pages 413-430, March.
    13. Alejandro Justiniano & Bruce Preston, 2010. "Monetary policy and uncertainty in an empirical small open‐economy model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 93-128, January.
    14. Armand Fouejieu & Scott Roger, 2013. "Inflation Targeting and Country Risk; An Empirical Investigation," IMF Working Papers 13/21, International Monetary Fund.
    15. Gumus, Inci, 2013. "Debt Denomination And Default Risk In Emerging Markets," Macroeconomic Dynamics, Cambridge University Press, vol. 17(5), pages 1070-1095, July.
    16. Granger, Clive W. J. & Terasvirta, Timo, 1993. "Modelling Non-Linear Economic Relationships," OUP Catalogue, Oxford University Press, number 9780198773207.
    17. Iva Petrova & Michael G. Papaioannou & Dimitri Bellas, 2010. "Determinants of Emerging Market Sovereign Bond Spreads; Fundamentals vs Financial Stress," IMF Working Papers 10/281, International Monetary Fund.
    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. Istvan Konya & Franklin Maduko, 2018. "Interest premium and external position: a time varying approach," CERS-IE WORKING PAPERS 1829, Institute of Economics, Centre for Economic and Regional Studies.
    2. Konya, Istvan & Maduko, Franklin, 2020. "Interest premium and external position: A state dependent approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 66(C).
    3. Hideaki Matsuoka, 2020. "Debt intolerance: Threshold level and composition," Working Papers on Central Bank Communication 014, University of Tokyo, Graduate School of Economics.

    More about this item

    Keywords

    Risk premium; PSTR model; open economy DSGE model;

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal 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

    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:sgh:kaewps:2018035. 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: (Jakub Muck). General contact details of provider: http://edirc.repec.org/data/kawawpl.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.

    If CitEc recognized a 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.

    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.