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

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  • 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
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    References listed on IDEAS

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    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.
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    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

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