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Economic volatility and sovereign yields’ determinants: a time-varying approach

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Using monthly data for 10 euro area countries between 1999:01 and 2015:12, we take a new three-step methodological approach: first, we inspect the key determinants of 10-year government bond yield spreads; second, we compute country-specific time-varying coefficient models of spreads’ determinants; third, we use these estimates as explanatory variables in panel regressions using output volatility as the dependent variable. We find that better fiscal positions or higher-than-expected economic growth prospects reduce the yield spreads, while increases in the VIX, bid-ask spread, debt-to-GDP ratio or real effective exchange rate appreciation increase the spreads. Moreover, the responsiveness of the yield spread determinants increased in the run-up to the global financial crisis. Finally, for the case of the budget balance and real growth (bid-ask spread, debt-to-GDP ratio, real effective exchange rate and VIX), the larger (higher) in absolute value the corresponding spread’s responsiveness, the lower (higher) the economic volatility.

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Fig. 1

Note: Output volatility measured as the centred 3-year standard deviation of rolling real GDP growth. Sovereign bond yield spreads relative to Germany’s

Fig. 2

Note: The horizontal axis represents years. The figure displays the average spread across the different countries in the sample

Fig. 3

Note: “median” denotes the average (median) value across all country estimates; “pctile_25” and “pctile_75” denote the first and third quartiles of the distribution of time-varying estimates across all countries, respectively

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  1. Ludwig (2014b) and Sibbertsen et al. (2014), for example, investigated the stochastic trending behaviour of the spreads. However, such analysis goes beyond the scope of this paper.

  2. The approach proposed by Schlicht (2003) is very similar to that used by Aghion and Marinescu (2008). The main difference is in the computation of the variances \( \sigma_{i}^{2} \). Aghion and Marinescu (2008) use the Markov Chain Monte Carlo (MCMC) method to approximate these variances, while Schlicht (2003) uses a method-of-moments estimator.

  3. We also computed two additional versions of the relative standard deviation using instead the detrended real GDP (from HP and WEO). We also checked both the standard deviation (baseline) measure and the relative counterpart for autocorrelation using the Q-Lung-box test. Using a rolling window may create autocorrelation, but the Q-Lung-box test systematically rejected the null of no first-order autocorrelation, suggesting that there is no autocorrelation. We also tried replacing our baseline proxy of output volatility (based on the simple standard deviation) with an alternative based on a GARCH model of the quarterly real GDP series. Results are kept qualitatively unchanged.

  4. We are aware of literature on the political economy determinants of government bond pricing. For instance, Huang et al. (2015) and Duyvesteyn et al. (2016) discuss the relevance of political risk in affecting government bonds. Exploring such aspects in greater detail goes beyond the scope of this paper. In addition, we also rely on a political economy proxy as instrument in the robustness section below when estimating using a two-stage least squares estimator.

  5. We thank the editor and an anonymous referee for these suggestions.

  6. The country list includes: Austria, Belgium, Finland, France, Greece, Ireland, Italy, Netherlands, Portugal and Spain.

  7. Note that we tested the time-series properties of the set of variables employed in the empirical section (results are omitted for reasons of parsimony) and found evidence pointing to panel stationarity. We relied on Im–Pesaran–Shin and the Maddala–Wu tests.

  8. Note that when estimating Eq. (1) with VIX included, time fixed effects are dropped. VIX captures the global factor that only varies over time but not across units.

  9. Removing Greece and Portugal increases the slope of the fitted line to 0.55 but lowers the R-square to 0.14.

  10. The reason for why X in Eq. (2) is a scalar in the TVC regressions relates to the simple fact that we want to specifically isolate the impact of a given variable. Alternatively, one could have estimated the TVC with all the regressors included simultaneously. Doing so does not qualitatively change the main results.

  11. We thank an anonymous referee for this suggestion.

  12. We thank the editor for this point.

  13. Moreover, we could explore yet additional variables that are known to affect output volatility such as the effect of oil price changes (in line with Wegener et al. 2016). However, taking our panel of countries, first none is an oil exporting country and, second any common exogenous effect is econometrically captured by the time effects.


  • Acemoglu D, Johnson S, Robinson J, Thaicharoen Y (2003) Institutional causes, macroeconomic symptoms: volatility, crises and growth. J Monet Econ 50:49–123

    Google Scholar 

  • Acharya V, Drechsler I, Schnabl P (2014) A Pyrrhic victory?—Bank bailouts and sovereign credit risk. J Finance 69(6):2689–2739

    Google Scholar 

  • Afonso A, Rault C (2015) Short and long-run behaviour of long-term sovereign bond yields. Appl Econ 47(37):3971–3993

    Google Scholar 

  • Afonso A, Arghyrou M, Kontonikas A (2014a) Pricing sovereign bond risk in the EMU area: an empirical investigation. Int J Finance Econ 19(1):49–56

    Google Scholar 

  • Afonso A, Gomes P, Taamouti A (2014b) Sovereign credit ratings, market volatility, and financial gains. Comput Stat Data Anal 76:20–33

    Google Scholar 

  • Aghion P, Marinescu I (2008) Cyclical budgetary policy and economic growth: what do we learn from OECD panel data? NBER Macroecon Annu 2007(22):251–278

    Google Scholar 

  • Alesina A, De Broeck M, Prati A, Tabellini G (1992) Default risk on government debt in OECD countries. Econ Policy 15:427–451

    Google Scholar 

  • Ang A, Longstaff F (2013) Systemic sovereign credit risk: lessons from the U.S. and Europe. J Monet Econ 60:493–510

    Google Scholar 

  • Ardagna S, Caselli F, Lane T (2004) Fiscal discipline and the cost of public debt service: some estimates for OECD Countries. ECB Working Paper 411

  • Arghyrou M, Kontonikas A (2012) The EMU sovereign debt crisis: fundamentals, expectations and contagion. J Int Financial Mark Inst Money 22:658–677

    Google Scholar 

  • Attinasi M-G, Checherita C, Nickel C (2009) What explains the surge in euro area sovereign spreads during the financial crisis of 2007-09? ECB Working Paper 1131

  • Barrios S, Iversen P, Lewandowska M, Setzer R (2009) Determinants of intra-euro-area government bond spreads during the financial crisis. European Commission, Economic Papers 388

  • Basse T, Kruse R, Wegener C (2017) The walking debt crisis. Department of Economics and Business Economics, Aarhus University, Aarhus

    Google Scholar 

  • Beber A, Brandt M, Kavajecz K (2009) Flight-to-quality or flight-to-liquidity? Evidence from the euro-area bond market. Rev Financial Stud 22:925–957

    Google Scholar 

  • Bernoth K, Erdogan B (2012) Sovereign bond yield spreads: a time-varying coefficient approach. J Int Money Finance 31(3):639–656

    Google Scholar 

  • Bernoth K, Von Hagen J, Schuknecht L (2004) Sovereign Risk Premia in the European Government Bond Market, European Central Bank Working Paper No. 369

  • Billio M, Caporin M (2010) Market linkages, variance spillovers, and correlation stability: empirical evidence of financial contagion. Comput Stat Data Anal 54:2443–2458

    Google Scholar 

  • Chiarella C, ter Saskia E, Xue-Zhong H, Wu E (2015) Fear or fundamentals? Heterogeneous beliefs in the European sovereign CDS market. J Empir Finance 32:19–34

    Google Scholar 

  • Christiansen C (2007) Volatility-spillover effects in European bond markets. Eur Financial Manag 13:923–948

    Google Scholar 

  • Codogno L, Favero C, Missale A (2003) Yield spreads on EMU government bonds. Econ Policy 18:211–235

    Google Scholar 

  • de Grauwe P, Ji Y (2013) Self-fulfilling crises in the Eurozone: an empirical test. J Int Money Finance 34:15–36

    Google Scholar 

  • de Santis R (2012) The euro area sovereign debt crisis: Safe haven, credit rating agencies and the spread of the fever from Greece, Ireland and Portugal. ECB Working Paper 1419

  • Debrun X, Kapoor R (2010) Fiscal policy and macroeconomic stability: automatic stabilizers work, always and everywhere. IMF Working Paper/10/111

    Google Scholar 

  • Driscoll JC, Kraay AC (1998) Consistent covariance matrix estimation with spatially dependent panel data. Rev Econ Stat 80(4):549–560.

    Article  Google Scholar 

  • Duyvesteyn J, Martens M, Verwijmeren P (2016) Political risk and expected government bond returns. J Empir Finance 38:498–512

    Google Scholar 

  • Elmendorf D, Mankiw N (1999) Government debt. In: Taylor J, Woodford M (eds) Handbook of macroeconomics, vol 1C, North-Holland, North-Holland, pp 1615–1669

    Google Scholar 

  • Engle R, Gallo G, Velucchi M (2012) Volatility spillovers in East Asian financial markets: a MEM-based approach. Rev Econ Stat 94(1):222–223

    Google Scholar 

  • Erickson T, Whited TM (2000) Measurement error and the relationship between investment and q. J Polit Econ 108:1027–1057

    Google Scholar 

  • Erickson T, Jiang CH, Whited TM (2014) Minimum distance estimation of the errors-in-variables model using linear cumulant equations. J Econom 183:211–221

    Google Scholar 

  • Fatás A, Mihov I (2001) Government size and automatic stabilizers. J Int Econ 55:3–28

    Google Scholar 

  • Fatás A, Mihov I (2013) Policy volatility, institutions, and economic growth policy volatility, institutions, and economic growth. Rev Econ Stat 95(2):362–376

    Google Scholar 

  • Favero C, Missale A (2012) Sovereign spreads in the euro area. Which prospects for a Eurobond? Econ Policy 27(70):231–273

    Google Scholar 

  • Favero C, Pagano M, von Thadden E-L (2010) How does liquidity affect government bond yields? J Financial Quant Anal 45:107–134

    Google Scholar 

  • Furceri D (2007) Is government expenditure volatility harmful for growth? A cross-country analysis. Fiscal Stud 28(1):103–120

    Google Scholar 

  • Furceri D, Karras G (2007) Country size and business cycle volatility: scale really matters. J Jpn Int Econ 21(4):424–434

    Google Scholar 

  • Gambacorta L, Hofmann B, Peersman G (2014) The effectiveness of unconventional monetary policy at the zero lower bound: a cross-country analysis. J Money Credit Bank 46:615–642

    Google Scholar 

  • Gerlach S, Schulz A, Wolff G (2010) Banking and sovereign risk in the Euro area. CEPR Discussion Paper No. 7833

  • Geyer A, Kossmeier S, Pichler S (2004) Measuring systemic risk in EMU government yield spreads. Rev Finance 8:171–197

    Google Scholar 

  • Henisz W (2013) Political Constraint Index (POLCON). Wharton School of the University of Pennsylvania, Philadelphia

    Google Scholar 

  • Huang T, Wu F, Yu J, Zhang B (2015) International political risk and government bond pricing. J Bank Finance 55:393–405

    Google Scholar 

  • Hui C, Chung T (2011) Crash risk of the euro in the sovereign debt crisis of 2009–2010. J Bank Finance 35:2945–2955

    Google Scholar 

  • Jones C, Lamont O, Lumsdaine R (1998) Macroeconomic news and bond market volatility. J Financial Econ 47:315–337

    Google Scholar 

  • Klomp J, de Hann J (2009) Political institutions and economic volatility. Eur J Polit Econ 25(3):311–326

    Google Scholar 

  • Lane PR (2003) The cyclicality of fiscal policy: evidence from the OECD. J Public Econ 87:2661–2675

    Google Scholar 

  • Leschinski C, Bertram P (2017) Time varying contagion in emu government bond spreads. J Financial Stab 29:72–91

    Google Scholar 

  • Ludwig A (2014a) A unified approach to investigate pure and wake-up-call contagion: evidence from the Eurozone’s first financial crisis. J Int Money Finance 48:125–146

    Google Scholar 

  • Ludwig A (2014b) Credit risk-free sovereign bonds under Solvency II: a cointegration analysis with consistently estimated structural breaks. Appl Financial Econ 24:811–823

    Google Scholar 

  • Manganelli S, Wolswijk G (2009) What drives spreads in the euro-area government bond market? Econ Policy 24:191–240

    Google Scholar 

  • Meinusch A, Tillmann P (2016) The macroeconomic impact of unconventional monetary policy shocks. J Macroecon 47:58–67

    Google Scholar 

  • Mody A (2009) From Bear Sterns to Anglo Irish: How Eurozone sovereign spreads related to financial sector vulnerability. IMF Working Paper 09/108

  • Rodrik D (1998) Who needs capital account convertibility? In: Kenen P (ed) Should the IMF pursue capital-account convertibility? Princeton Essays in International Finance, No 207

  • Saka O, Fuertes A, Kalotychou E (2015) ECB policy and Eurozone fragility: was De Grauwe right? J Int Money Finance 54:168–185

    Google Scholar 

  • Schlicht E (1985) Isolation and aggregation in economics. Springer, Berlin

    Google Scholar 

  • Schlicht E (1988) Variance estimation in a random coefficients model. Paper presented at the Econometric Society European Meeting Munich 1989.\_variance-estimation-inrandom-coeff-model.pdf. Accessed Mar 2017

  • Schlicht E (2003) Estimating time-varying coefficients with the VC program. University of Munich Discussion Paper 2003–06

  • Schlicht E, Ludsteck J (2006) Variance estimation in a random coefficients model. IZA Discussion Paper No. 2031

  • Sgherri S, Zoli E (2009) Euro area sovereign risk during the crisis. IMF Working Paper 09/222

  • Sibbertsen P, Wegener C, Basse T (2014) Testing for a break in the persistence in yield spreads of EMU government bonds. J Bank Finance 41:109–118

    Google Scholar 

  • Talvi E, Végh C (2000) Tax base variability and procyclical fiscal policy. NBER Working Paper 7499

  • Wegener C, Basse T, Kunze F, von Mettenheim H-J (2016) Oil prices and sovereign credit risk of oil producing countries: an empirical investigation. Quant Finance 16:1961–1968

    Google Scholar 

  • Whaley R (2000) The Investor fear gauge. J Portf Manag 26:12–17

    Google Scholar 

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UECE is supported by FCT (Fundação para a Ciência e a Tecnologia, Portugal).

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Correspondence to João Tovar Jalles.

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We thank the editor and an anonymous referee for very useful comments and suggestions. The opinions expressed herein are those of the authors and do not necessarily reflect those of their employers.



See Tables 9, 10 and 11.

Table 9 Summary statistics monthly data
Table 10 Data definition and sources
Table 11 Summary statistics annual data

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Afonso, A., Jalles, J.T. Economic volatility and sovereign yields’ determinants: a time-varying approach. Empir Econ 58, 427–451 (2020).

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