Afonso, A. and Jalles J.T. (2011), “Growth and Productivity: The Role of Government Debt,” School of Economics and Management, Technical University of Lisbon, Working Paper No. 13/2011 (Lisbon: Technical University)
Arora, V. B., and M.D. Cerisola (2000), “How Does U.S Monetary Policy Influence Economic Conditions in Emerging Markets?” IMF Working Paper No. 00/148
Audrino, F. and E. De Giorgi (2007), “Beta Regimes for the Yield Curve”, Journal of Financial Econometrics, Vol. 5, No. 3, pp. 456–490
Baldacci E. and Kumar M., (2010), “Fiscal Deficits, Public Debt, and Sovereign Bond Yields”, IMF Working Paper 10/184 (Washington: International Monetary Fund).
Baldacci, E., G. Sanjeev, and A. Mati (2008), “Is It (Still) Mostly Fiscal? Determinants of Sovereign Spreads in Emerging Markets”, IMF Working Paper 08/259 (Washington: International Monetary Fund).
Bank for International Settlements (2007), “Financial Stability and Local Currency Bond Markets”, Committee on the Global Financial System Papers No. 28, June.
Bellas, D., M. Papaioannou, and I. Petrova (2010), “Determinants of Emerging Market Sovereign Bond Spreads: Fundamentals vs Financial Stress”, IMF Working Paper No. 10/281 (Washington: International Monetary Fund).
Brooks, R. D., R.W. Faff and M. Mckenzie (2002), “Time-varying Country Risk: An Assessment of Alternative Modelling Techniques”, The European Journal of Finance, Vol. 8, pp. 249–274.
Caceres, C., V. Guzzo, and M. Segoviano (2010), “Sovereings Spreads: Global Risk Aversion, Contagion or Fundamentals?” IMF Working Paper No. 10/120.
Chen, S. and N. Huang (2007), “Estimates of the ICAPM with Regime-Switching Betas: Evidence from Four Pacific Rim Economies”, Applied Financial Economics, Vol. 17, pp. 313–327.
Dailami, M., P. R. Masson, and J.J. Padou (2008), “Global Monetary Conditions Versus Country-Specific Factors in the Determination of Emerging Market Debt”, Journal of International Money and Finance, Vol. 27, pp. 1325–1336.
Davies, R.B. (1977), “Hypothesis Testing when a Nuisance Parameter is Only Present Under The Alternative, Biometrika, Vol. 64, pp. 247–54.
Dell’Erba, S. and Sola, S. (2011), “Expected Fiscal Policy and Interest Rates in Open Economy,” Graduate Institute of International and Development Studies Working Paper No. 07/2011 (Geneva: The Graduate Institute).
Edwards, S. (1984), “LDC’s Foreign Borrowing and Default Risk: An Empirical Investigation 1976—1980”, NBER Working Paper No. 1172.
Eichengreen, B. and A. Mody (2000), “What Explains Changing Spreads on Emerging Market Debt?”, in Capital Flows and the Emerging Economies: Theory, Evidence, and Controversies, edited by S. Edwards, University of Chicago Press.
Galagedera, D. and R. Faff (2004), “Modeling the Risk And Return Relation Conditional on Market Volatility and Market Conditions”, International Journal of Theoretical and Applied Finance, Vol. 8, No. 1, pp. 75–95.
Gonzalez-Rozada, M. and E. Levy-Yeyati (2008), “Global Factors And Emerging Market Spreads”, The Economic Journal, Vol. 118 (November), pp. 1917–1936.
Hansen, B. E. (1996), “Inference When a Nuisance Parameter is not Identified Under The Null Hypothesis,” Econometrica, Vol. 64, pp. 413–430.
Hartelius, K., K. Kashiwase, and L. Kodres (2008), “Emerging Market Spread Compression:Is it Real or is it Liquidity?”, IMF Working Paper No. 08/10 (Washington: International Monetary Fund).
International Monetary Fund (2004), Global Financial Stability Report: Market Developments and Issues, April (Washington: International Monetary Fund).
Johansson, A. (2009), “Stochastic Volatility and Time-Varying Country Risk in Emerging Markets”, The European Journal of Finance, Vol. 15, No. 3, April, 337–363.
Kamin, S. and K. von Kleist (1999), “The Evolution and Determinants of Emerging Market Credit Spreads in the 1990s’” BIS Working Paper 68 (Basel: Bank for International Settlements).
Korkmaz, T. E. I. Çevik, and S. Gürkan (2010), “Testing of the International Capital Asset Pricing Model With Markov Switching Model in Emerging Markets” Investment Management and Financial Innovations, Vol. 7, Issue 1.
Laubach T. (2009), “New Evidence on the Interest Rate Effects of Budget Deficits and Debt,” Journal of the European Economic Association, Vol. 7, No. 4, pp. 858–885
Longstaff, F., J. Pan, L. H. Pedersen, and K. J. Singleton (2011), :”How Sovereign is Sovereign Credit Risk?”, American Economic Journal: Macroeconomies, 3, pp. 75–103.
McGuire, P. and M. Schrijvers (2003), “Common Factors in Emerging Market Spreads”, BIS Quarterly Review, December 2003 (Basel: Bank for International Settlements).
Mihaljek, D., M. Scatigna, and A. Villar (2002), “The Development of Bond Markets in Emerging Economies,” BIS Papers Number 11 (Basel: Bank for International Settlements).
Min, H.G. (1998), “Determinants of Emerging Market Bond Spread: Do Economic Fundamentals Matter?” World Bank Policy Research Working Paper No. 1899 (Washington: The World Bank).
Modigliani, F. (1961), “Long-run Implications of Alternative Fiscal Policies and the Burden of the National Debt,” Economic Journal, Vol. 71, pp. 730–755.
Mundell, R.A. (1963), “Capital Mobility and Stabilization Policy Under Fixed and Flexible Exchange Rates,” Canadian Journal of Economics, Vol. 29 No. 4, pp. 475–485.
Peiris, S.J. (2010). “Foreign Participation in Emerging Markets’ Local Currency Bond Markets,” IMF working Paper 10/88 (Washington: International Monetary Fund).
Pesaran, M. H. (2004). “General Diagnostic Tests for Cross Section Dependence in Panels,” Cambridge Working Papers in Economics No. 0435 (Cambridge: Cambridge University).
Pesaran, M. H., 2006. “Estimation and Inference in Large Heterogeneous Panels With A Multifactor Error Structure,” Econometrica, Vol. 74, No. 4, pp. 967–1012.
Reinhart, V. and Sack, B. (2000), “The Economic Consquences of Disappearing Government Debt,” Brookings Papers on Economic Activity, Economic Studies Program, Vol. 31, pp. 163–220 (Washington: Brookings Institution).
Rowland, P. and J. L. Torres (2004), “Determinants of Spread and Creditworthiness for Emerging Market Sovereign Debt: A Panel Data Study”, Borradores de Economia 295, Banco de la Republica de Colombia.
Sløk, T. and M. Kennedy (2004), “Factors Driving Risk Premia” OECD Working Paper No. 385 (Paris: Organization for Economic Cooperation and Development).
Uribe, M., and V.Z. Yue (2006), “Country Spreads and Emerging Countries: Who drives Whom?” Journal of International Economics, Vol. 69, pp. 6–36.
We thank Carlo Cottarelli, Phil Gerson, Martine Guerguil, and Paolo Mauro for helpful comments and discussions. We are grateful for comments by Nina Budina, Lorenzo Forni, Fuad Hasanov, Joao Tovar Jalles, Bruno Momont, and Federico Gabriel Presciuttini. We would like to thank the Economist Intelligence Unit and in particular Michael Schaeffer for providing data on market expectations of fiscal variables, inflation and growth. Petra Dacheva and Raquel Gomez-Sirera provided excellent research assistance. All remaining errors are our own.
The Chicago Board Options Exchange Volatility Index (VIX) is a measure of the market’s expectation of stock-market volatility over the next 30-day period. It is a weighted blend of prices for a range of options on the S&P 500 index. See http://www.cboe.com/micro/VIX/vixintro.aspx.
Studies using sovereign foreign currency spreads are more widespread. Many empirical studies have focused on the impact of domestic factors, including indicators of external vulnerability like external debt, debt service or current account (Edwards, 1984; Cantor and Packer, 1996); fiscal variables, like fiscal debt and deficits (Cantor and Packer, 1996; Rowland and Torres, 2004) or their composition (Akitobi and Stratmann, 2008); and other macroeconomic variables like inflation, the terms of trade and the real exchange rate (Min, 1998).
The development of the institutional structure and microstructure of bond markets, as well as the improvement of financial markets more generally, has also played a key role. See Mihaljek and others (2002).
The literature is inconclusive regarding the effects of the global interest rate environment on international spreads in emerging economies. Arora and Cerisola (2000) and Hartelius and others (2008) find a positive correlation, Eichengreen and Mody (2000), McGuire and Schrijvers (2003), and Uribe and Yue (2006) find a negative relationship, while Kamin and von Kleist (1999), Sløk and Kennedy (2004), and Baldacci and others (2008) find the relationship insignificant. The existing literature on domestic bond yields in emerging economies has not focused on the effects of global interest rates.
A Hausman (1978) test was conducted to check whether a fixed effects model is preferable to a random effects model. The hypothesis that the individual-level effects are adequately captured by a random effects model can be rejected at the 1 percent level of significance.
Due to data limitations, this variable does not distinguish between flows into sovereign and corporate bonds.
The VIX has been traditionally used in the literature as measure of global risk aversion. See for example McGuire and Schrijvers (2003), IMF (2004), Gonzales-Rozada and Levy-Yeyati (2008), Hartelius and others (2008), Bellas and others (2010), Caceres and others (2010), Baldacci and Kumar (2010), and Longstaff and others (2011).
The motivation for exploring the behavior of bond yields in low and high global risk environments draws on the financial literature and the estimation of time-varying αs (the asset’s sensitivity to market risk) when determining an optimal portfolio under the capital asset pricing model (CAPM). Evidence on the state dependency of the αs has been found for both advanced (Huang, 2001; Brooks and others, 2002; Galagedera and Faff, 2004; Audrino and De Giorgi, 2007) and emerging economies (Chen and Huang, 2007; Johansson, 2009; Korkmaz and others, 2010).
While this paper uses data only for emerging market economies, we are not aware of any study that uses this threshold methodology in the context of domestic bond yields in advanced countries.
A common criticism of the fixed effects model when estimating long-term bond yields has been that it treats data as if they are cross-sectionally independent although in open economies with integrated capital markets, common factors are likely present, affecting all interest rates simultaneously (Dell’Erba and Sola, 2011). We run the cross section dependence (CD) test (Pesaran, 2004) and find significant evidence of cross sectional dependence. We therefore estimated equation (1) with the common correlated effects mean group (CCEMG) estimator (Pesaran, 2006), we found that the results are very similar, except that the expectations of the public debt-to-GDP ratio become insignificant. The CCEMG estimator may however not be well suited for our analysis, since the sample is very unbalanced and T and N are relatively small. This is why we did not give it more prominence in the paper.
Peiris (2010) shows that foreign participation in the local bond markets, measured by the share of the outstanding stock of government securities held by non residents, is a significant determinant of long-term yields. These data are only available quarterly, so that they could not be used as a robustness check in the above regression.
Global liquidity, proxied by the US 10 year bond yield is also not found to be significant. This could be due to collinearity with domestic treasury bills, since in small open economies monetary policy is affected by external liquidity. This does not affect the reliability or predictive power of the model as a whole. Furthermore, we included exchange rate expectations one-year ahead from Consensus Forecasts, but did not find that it was significant. This could be due to the fact that inflation is capturing part of this effect.
We thank Joao Tovar Jalles for making his STATA codes for the Hansen panel threshold methodology available to us (see Afonso and Jalles, 2011).
The corresponding Supremum Wald-test is 70.76, with a p-value is 0.018, indicating a significant sample break for the full sample. This threshold is robust to adding different dependent variables, including money market rates instead of T-bill rates.
Results of robustness checks are available from the authors upon request.