Hostname: page-component-cd9895bd7-7cvxr Total loading time: 0 Render date: 2024-12-22T18:40:01.940Z Has data issue: false hasContentIssue false

THE NONLINEAR NATURE OF COUNTRY RISK AND ITS IMPLICATIONS FOR DSGE MODELS

Published online by Cambridge University Press:  03 August 2018

Michał Brzoza-Brzezina
Affiliation:
Narodowy Bank Polski and SGH Warsaw School of Economics
Jacek Kotłowski*
Affiliation:
Narodowy Bank Polski and SGH Warsaw School of Economics
*
Address correspondence to: Jacek Kotłowski, Narodowy Bank Polski Economic Analysis Department ul. Świętokrzyska 11/21 00-919 Warszawa, Poland; e-mail: [email protected]

Abstract

Country risk premia can substantially affect macroeconomic dynamics. We concentrate on one of their most important determinants—a country’s net foreign asset (NFA) position and—in contrast to the existing research—investigate its nonlinear link to risk premia. The importance of this particular nonlinearity is two-fold. First, it allows to identify the NFA level above which the elasticity becomes much (possibly dangerously) higher. Second, such a nonlinear relationship is a standard ingredient of dynamic stochastic general equilibrium (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 nonlinearity 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.

Type
Articles
Copyright
© Cambridge University Press 2018

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

The views expressed herein are ours and not necessarily those of Narodowy Bank Polski or the Warsaw School of Economics. We would like to thank the participants of the Dynare conference in Rome, Computing in Economics and Finance conference in Bordeaux, Ecomod conference in Lisbon, the Conference on Computational and Financial Econometrics in Sevilla and the seminar at the Narodowy Bank Polski for valuable comments. Comments received from Johannes Pfeifer, the associate Editor and an anonymous referee are gratefully acknowledged as well.

References

REFERENCES

Adolfson, Malin, Laseen, Stefan, Linde, Jesper, and Villani, Mattias (2007) Bayesian estimation of an open economy DSGE model with incomplete pass-through. Journal of International Economics 72 (2), 481511.CrossRefGoogle Scholar
Baldacci, Emanuele and Kumar, Manmohan S. (2010) Fiscal Deficits, Public Debt, and Sovereign Bond Yields. IMF working papers 10/184, International Monetary Fund.CrossRefGoogle Scholar
Bellas, Dimitri, Papaioannou, Michael G, and Petrova, Iva (2010) Determinants of Emerging Market Sovereign Bond Spreads: Fundamentals vs. Financial Stress. IMF Working papers 10/281, International Monetary Fund.CrossRefGoogle Scholar
Benczur, Peter and Konya, Istvan (2015) Interest Premium, Sudden Stop, and Adjustment in a Small Open Economy. IEHAS discussion papers 1505, Institute of Economics, Centre for Economic and Regional Studies, Hungarian Academy of Sciences.Google Scholar
Christoffel, Kai, Coenen, Günter, and Warne, Anders (2008) The New Area-Wide Model of the Euro Area: A Micro-Founded Open-economy Model for Forecasting and Policy Analysis. Working paper series 0944, European Central Bank.Google Scholar
Ciocchini, Francisco, Durbin, Erik, and Ng, David T. C. (2003) Does corruption increase emerging market bond spreads? Journal of Economics and Business 55 (5–6), 503528.Google Scholar
Dohmen, Thomas, Enke, Benjamin, Falk, Armin, Huffman, David, and Sunde, Uwe (2016) Patience and the Wealth of Nations. Working papers 2016-012, Human Capital and Economic Opportunity Working Group.Google Scholar
Escribano, Álvaro and Jordá, Oscar (2001) Testing nonlinearity: Decision rules for selecting between logistic and exponential STAR models. Spanish Economic Review 3 (3), 193209.CrossRefGoogle Scholar
Fagan, Gabriel and Gaspar, Vitor (2007) Adjusting to the euro. Working paper series 716, European Central Bank.Google Scholar
Falk, Armin, Becker, Anke, Dohmen, Thomas, Enke, Benjamin, Huffman, David B., and Sunde, Uwe (2015) The Nature and Predictive Power of Preferences: Global Evidence. IZA discussion papers 9504, Institute for the Study of Labor (IZA).CrossRefGoogle Scholar
Ferrucci, Gianluigi (2003) Empirical Determinants of Emerging Market Economies’ Sovereign Bond Spreads. Bank of England working papers 205, Bank of England.CrossRefGoogle Scholar
Fouejieu, Armand and Roger, Scott (2013) Inflation Targeting and Country Risk: An Empirical Investigation. IMF working papers 13/21, International Monetary Fund.CrossRefGoogle Scholar
Garcia-Cicco, Javier, Pancrazi, Roberto, and Uribe, Martin (2010) Real business cycles in emerging countries? American Economic Review 100 (5), 25102531.CrossRefGoogle Scholar
González, Andrés, Teräsvirta, Timo, and van Dijk, Dick (2005) Panel Smooth Transition Regression Models. SSE/EFI Working paper series in economics and finance 604, Stockholm School of Economics.Google Scholar
Granger, Clive W. J. and Teräsvirta, Timo (1993) Modelling Non-Linear Economic Relationships, Oxford: Oxford University Press.Google Scholar
Gumus, Inci (2013) Debt denomination and default risk in emerging markets. Macroeconomic Dynamics 17 (5), 10701095.CrossRefGoogle Scholar
Hansen, Bruce E. (1996) Inference when a nuisance parameter is not identified under the null hypothesis. Econometrica 64 (2), 413430.CrossRefGoogle Scholar
IMF (2013) External Balance Assessment (EBA) Methodology: Technical Background. Background paper, International Monetary Fund.Google Scholar
Justiniano, Alejandro and Preston, Bruce (2010) Monetary policy and uncertainty in an empirical small open-economy model. Journal of Applied Econometrics 25 (1), 93128.CrossRefGoogle Scholar
Lane, Philip R. and 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 55 (2), 263294.CrossRefGoogle Scholar
Luukkonen, Ritva, Saikkonen, Pentti, and Teräsvirta, Timo (1988) Testing linearity against smooth transition autoregressive models. Biometrika 75 (3), 491499.CrossRefGoogle Scholar
Miyamoto, Wataru and Nguyen, Thuy Lan (2017) Business cycles in small open economies: Evidence from panel data between 1900 and 2013. International Economic Review 58 (3), 10071044.CrossRefGoogle Scholar
Qian, Zongxin, Wang, Wendun, and Ji, Kan (2017) Sovereign credit risk, macroeconomic dynamics, and financial contagion: Evidence from Japan. Macroeconomic Dynamics 21 (08), 20962120.CrossRefGoogle Scholar
Schmitt-Grohe, Stephanie and Uribe, Martin (2003) Closing small open economy models. Journal of International Economics 61 (1), 163185.CrossRefGoogle Scholar
Smets, Frank and Wouters, Raf (2005) Comparing shocks and frictions in US and euro area business cycles: A Bayesian DSGE approach. Journal of Applied Econometrics 20 (2), 161183.CrossRefGoogle Scholar
Teräsvirta, Timo (1994) Specification, estimation, and evaluation of smooth transition autoregressive models. Journal of the American Statistical Association 89 (425), 208218.Google Scholar