## 1. Descriptive Statistics

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---

### Introduction and context
- Financial markets’ perception of credit risks in emerging economies improved sharply over the last half decade.
- The spread of the composite Emerging Market Bond Index Global (EMBIG) calculated by JP Morgan tightened by more than 500 basis points between mid-2002 and August 2007 (Baldacci, 2007).
- The downward trend was only partially reversed since the onset of the subprime-induced financial crisis (IMF, 2008).
- Credit Default Swap (CDS) spreads also fell drastically over the last five years despite the recent cyclical uptick.
- EMBIG index characteristics:
  - Introduced in January 1998.
  - Includes countries rated BBB+ or lower by Standard & Poor’s.
  - Countries included are both middle-income and low-income economies that have undergone at least an episode of debt restructuring.
  - EMBIG is a global market benchmark for emerging economies’ credit risk assessment.
- CDS vs EMBIG interpretation:
  - CDS spreads can be viewed as the marginal cost of debt.
  - The EMBIG sub-index for a country is more representative of the average cost of traded debt.
  - According to Singh and Andritzky (2005), CDS spreads are a leading indicator of borrowing costs during crisis periods, while the average cost is a better proxy for the sovereign risk in the absence of default.

### Literature and gaps
- Prior literature attributes tightening of emerging market spreads to:
  - Sound macroeconomic policies that brought inflation under control (including through more independent monetary authorities), reduced output volatility, and significant reductions in public and external debt (Ciarlone, Piselli, and Trebeschi, 2008).
  - Higher commodity prices and favorable liquidity conditions that lowered risk and resulted in large capital flows (Hartelius, Kashiwase, and Kodres, 2008).
  - Development of capital markets, which helped diversify production chain risks (Baldwin, 2006).
- The impact of political and fiscal factors and their interaction with global financial conditions has been relatively limited in prior analysis.

### Research design and sample
- Constructs a comprehensive measure of political risk and introduces fiscal variables into a model of spreads.
- Sample: 30 emerging market economies.

### Theoretical framework: sovereign default decision with political and fiscal risks
- Government welfare U = U(c, D, C) where c = per capita output, D = loan obtained, C = default cost; assumptions: 0/>∂∂cU, 0/<∂∂CU, 0/>∂∂DU.
- Non-explosive debt dynamics constraint: dgrs)(−≥ (equation (2)), with s = primary government budget surplus, revenue = constant share of output c, r = interest rate, g = growth rate, d = debt-to-output ratio.
- Default probability p>0 when expected cost E(C) satisfies D
CE
p
)(
1−= (equation (3)). E(C)=f(L) with f’>0 and f’’<0 (equation (4)).
- Loss variable L = c + R (equation (5)), with R = reputation capital R = φ(c, ρ) (equation (6)), where 0/>∂∂cR and 0/<∂∂ρR (higher political risk ρ reduces R).
- Combining gives default probability p = D
Rcf
)(
1
+
−= (equation (7)) with signs: 0/<∂∂cp, 0/>∂∂Dp, and 0/>∂∂ρp.
- Implication: probability of default (and sovereign spread) is a positive function of political risk and public debt levels, and a negative function of macroeconomic health.

### Empirical model specification and data
- Panel specification: ititiit uXY++=βα, i=1,....N; t=1,...T  (equation (8)), where Yit = logarithm of foreign currency bond spreads (annual averages); Xit = explanatory variables.
- Estimators: fixed and random effects; Wu-Hausman test to choose; instrumental variables via 2-stage least squares and Generalized Method of Moments to address endogeneity/omitted variables.
- Main explanatory blocks included in Xit:
  - Solvency and liquidity: external reserves as percentage of GDP; inflation rate (logged); current account balance; economic growth.
  - Global financial conditions: US policy interest rate (FED Funds); VIX stockmarket volatility index.
  - Fiscal vulnerability: overall fiscal balance as share of GDP; public investment ratio to GDP.
  - Political risk: PRI (principal component index combining World Bank governance and Heritage Foundation economic freedom indicators, centered on zero with positive values when political risk is low). Robustness: ICRG political risk variable and FRPRI ranging between -2.5 (highest risk) and +2.5 (lowest risk). Sub-indexes: FRPOL (political violence), FRTRA (transfer), FREXP (expropriation).
- Data:
  - Sample: spreads on 30 emerging market countries from EMBIG, period 1997-2007; annual spreads are period averages.
  - Macroeconomic variables: WEO database. Financial variables: Bloomberg. Fiscal variables: GFS database. Political risk variables: World Bank governance database and Heritage Foundation.
  - Note: "20 percent increase in the political risk index is equivalent to moving from the bottom quintile to the medium-risk range of the country distribution."

### Key empirical findings
- Political risk and spreads:
  - Lower levels of political risk are associated with reduced spreads.
  - Consistent with progress in reducing political instability, consolidating nascent democratic institutions, and reducing government interference in the economy (Eichengreen and Leblang, 2006).
- Fiscal policy and spreads:
  - Fiscal consolidation lowers credit spreads considerably, especially in countries that experienced a prior default.
  - Composition matters:
    - High public investment contributes to lower spreads as long as it does not increase the fiscal deficit.
    - Financial markets view public investment positively in infrastructure-constrained economies.

### Estimation results (selected quantitative findings)
- Hausman test: rejected the fixed effects model at 1 percent significance level.
- Table 3 (random effects estimates, dependent variable: Annual Mean Spread) — selected coefficients (robust standard errors in parentheses; significance * 10%, ** 5%, *** 1%):
  - PRI: -0.168 (0.050)*** in column (1); -0.179 (0.052)*** in (2); -0.1575 (0.070)** in (3); -0.161 (0.06)*** in (4); -0.159 (0.013)*** in (5).
  - Fiscal Balance: -7.76 (1.512)*** in (1); -7.83 (1.970)*** in (2); -4.297 (2.106)** in (3); -4.708 (2.05)** in (4); -5.59 (1.836)*** in (5).
  - Public Investment: -0.054 (0.026)** in (1); -0.078 (0.025)*** in (2); -0.072 (0.032)** in (3); -0.065 (0.02)** in (4); -0.06 (0.026)** in (5).
  - FED Funds Rate: -0.007 (0.030) in (1); -0.007 (0.031) in (2); -0.001 (0.032) in (3).
  - Log inflation: 0.178 (0.082)** in (1); 0.177 (0.083)** in (2); 0.169 (0.085)** in (3).
  - Reserves: -1.664 (0.875)** in (1); -2.15 (0.795)*** in (2); -2.34 (0.785)*** in (3).
  - Current account balance: -1.28 (0.675)** in (1); -1.66 (0.61)*** in (2); -1.81 (0.606)*** in (3).
  - TOT: -0.011 in (1); -0.010 in (2); -0.011 in (3) (standard errors and significance reported in table).
- Sample sizes and fit:
  - N = 188, 245, 173, 128 across columns (varies by specification).
  - Overall R-Square = 0.21, 0.17, 0.27, 0.46 (column 4: full specification explains 46 percent of variation).
- Interpretation and elasticities reported in text:
  - "A 10 percent increase in our political risk index leads to a 10 basis point increase in spreads."
  - "A 10 percent increase in the fiscal surplus reduces spreads by 2 percent, implying that one percent of GDP improvement in the primary balance can help decrease spreads by about 30-40 basis points."
  - Public investment coefficient significant and negative, but the fiscal balance effect is several orders of magnitude larger; deficit-financed investment does not lower spreads.
- Interaction effects (columns 5 and 6):
  - Slope dummies for high market volatility (dummy = 1 if VIX > 25) and prior default history (dummy = 1 in year of default and subsequent years).
  - Political factors do not matter more during periods of financial stress or in countries with prior default history (interaction terms with PRI insignificant).
  - Fiscal balance matters more for countries with prior default or in high volatility: e.g., in countries with prior default, a 1 percent of GDP increase in the fiscal deficit would increase spreads by about 80 basis points (textual statement).

### Robustness analysis
- Methods: FGLS to account for heteroskedasticity across panels; IV using debt-to-GDP instrument for overall fiscal balance with 2SLS and GMM. Results: political and fiscal variables remain significant and robust.
- Alternative solvency/liquidity/fiscal measures: higher real growth → lower spreads; high debt-to-GDP → higher spreads.
- Political risk components (Table 5, random effects): effects on spreads when replacing PRI with Ferrari and Rolfini subcomponents:
  - Rrexpr (expropriation): -0.52, R-Square 0.46, Obs 128 (standard error (0.25)** reported).
  - Rrtra (transfer): -0.069, R-Square 0.33, Obs 128 (0.21).
  - Rrpol (political violence): -0.22, R-Square 0.37, Obs 128 (0.26).
  - PolRisk (ICRG-based): -0.038, R-Square 0.43, Obs 172 (0.01)***.
- Key robustness conclusion: expropriation (creeping expropriation) appears most closely related to bond spreads; ICRG political risk variable also highly significant.

### Conclusions and policy implications
- Empirical findings (30 EMs, 1997-2007): political risk factors, including expropriation risk, significantly raise sovereign spreads; fiscal variables are more important with larger impact on spreads.
- Fiscal health matters:
  - High deficits or debt increase default risk and spreads.
  - Increasing capital spending lowers spreads only if it does not widen the fiscal deficit.
- Asymmetry: sensitivity of spreads to fiscal risk is larger for countries with previous defaults (reputational consequences).
- Policy implications:
  - Fiscal prudence is crucial to reduce borrowing costs: country-specific fiscal health is important despite global financial conditions; markets punish underestimated fiscal risks via wider spreads, especially for countries with poor fiscal track records.
  - Business climate and institutions (political stability) matter: poor political stability and weak institutions raise perceived country risk, reduce capital inflows, depress investment, and can lower economic growth.

*Source: IMF working paper content unit _wp08259 (Sections II–VII summary as provided).*

### 1. Descriptive Statistics...............................................................................................

### 1. Descriptive Statistics...............................................................................................

### Introduction and context
- Financial markets’ perception of credit risks in emerging economies improved sharply over the last half decade.
- The spread of the composite Emerging Market Bond Index Global (EMBIG) calculated by JP Morgan tightened by more than 500 basis points between mid-2002 and August 2007 (Baldacci, 2007).
- The downward trend was only partially reversed since the onset of the subprime-induced financial crisis (IMF, 2008).
- Credit Default Swap (CDS) spreads also fell drastically over the last five years despite the recent cyclical uptick.
- EMBIG index characteristics:
  - Introduced in January 1998.
  - Includes countries rated BBB+ or lower by Standard & Poor’s.
  - Countries included are both middle-income and low-income economies that have undergone at least an episode of debt restructuring.
  - EMBIG is a global market benchmark for emerging economies’ credit risk assessment.
- CDS vs EMBIG interpretation:
  - CDS spreads can be viewed as the marginal cost of debt.
  - The EMBIG sub-index for a country is more representative of the average cost of traded debt.
  - According to Singh and Andritzky (2005), CDS spreads are a leading indicator of borrowing costs during crisis periods, while the average cost is a better proxy for the sovereign risk in the absence of default.

### Literature and gaps
- Literature attributes tightening of emerging market spreads to:
  - Sound macroeconomic policies that brought inflation under control (including through more independent monetary authorities), reduced output volatility, and significant reductions in public and external debt (Ciarlone, Piselli, and Trebeschi, 2008).
  - Higher commodity prices and favorable liquidity conditions that lowered risk and resulted in large capital flows (Hartelius, Kashiwase, and Kodres, 2008).
  - Development of capital markets, which helped diversify production chain risks (Baldwin, 2006).
- The impact of political and fiscal factors and their interaction with global financial conditions has been relatively limited in prior analysis.

### Research design and sample
- This paper constructs a comprehensive measure of political risk and introduces fiscal variables into a model of spreads.
- Sample: 30 emerging market economies.

### Key empirical findings
- Political risk and spreads:
  - Lower levels of political risk are associated with reduced spreads.
  - This finding is consistent with progress in reducing political instability, consolidating nascent democratic institutions, and reducing government interference in the economy (Eichengreen and Leblang, 2006).
- Fiscal policy and spreads:
  - Fiscal consolidation lowers credit spreads considerably, especially in countries that experienced a prior default.
  - Composition matters:
    - High public investment contributes to lower spreads as long as it does not increase the fiscal deficit.
    - Financial markets view public investment positively in infrastructure-constrained economies.

### Organization of the paper (as provided)
- Section II provides an overview of the literature on the determinants of sovereign bond spreads in emerging market countries and highlights that the link between political risk, fiscal factors, and sovereign spreads has been neglected so far.

*Source: _wp08259 - 1. Descriptive Statistics...............................................................................................*

### Section III discusses a framework for modeling debt default decisions taking into account the

### _wp08259 - Section III discusses a framework for modeling debt default decisions taking into account the

### Literature review: determinants of sovereign spreads
- Key country-specific economic determinants highlighted in prior literature: external debt, debt service, current account balance, international reserves, investment ratio (Edwards, 1984).  
- Additional macro variables found important: domestic inflation rate, net foreign assets, terms of trade index, real exchange rate (Min, 1998).  
- Creditworthiness and credit ratings are important determinants of sovereign debt costs; ratings themselves are influenced by macro fundamentals.  
- Global factors and contagion: interest rate expectations, volatility, and systemic events account for large shares of spread dynamics in several studies (Hartelius, Kashiwase, and Kodres (2008); Gonzales-Rosada and Levy-Yeyati (2006)).  
- Structural-model strand: theoretical frameworks link default risk to opportunity costs of repudiation, social costs (market exclusion), market liquidity, funding costs, and interest rate curve slope (Eaton and Gersovitz (1981); Kulatilaka and Marcus (1987); Westphalen (2001)).  
- Fiscal stability: mixed evidence—many empirical studies find fiscal variables not significant once macro controls are included; exceptions show fiscal deficits and public debt levels can affect spreads and ratings (Hallerberg and Wolff (2008); Akitoby and Stratman (2006)). Composition of consolidation matters: expenditure compression (especially current relative to capital) associated with lower spreads vs. deficit reduction via tax increases.  
- Political risks: limited empirical assessment historically due to data constraints. Studies find links between electoral uncertainty, cabinet reshuffles, and spreads (Pantzalis et al. (2001); Stein and Streb (2004); Moser (2007)), but medium-term effects of political violence, transfer, and expropriation risks are less explored.

### Theoretical framework: sovereign default decision with political and fiscal risks
- Government welfare U = U(c, D, C) where c = per capita output, D = loan obtained, C = default cost; assumptions: 0/>∂∂cU, 0/<∂∂CU, 0/>∂∂DU.  
- Non-explosive debt dynamics constraint: dgrs)(−≥ (equation (2)), with s = primary government budget surplus, revenue = constant share of output c, r = interest rate, g = growth rate, d = debt-to-output ratio.  
- Default probability p>0 when expected cost E(C) satisfies D
CE
p
)(
1−= (equation (3)). E(C)=f(L) with f’>0 and f’’<0 (equation (4)).  
- Loss variable L = c + R (equation (5)), with R = reputation capital R = φ(c, ρ) (equation (6)), where 0/>∂∂cR and 0/<∂∂ρR (higher political risk ρ reduces R).  
- Combining gives default probability p = D
Rcf
)(
1
+
−= (equation (7)) with signs: 0/<∂∂cp, 0/>∂∂Dp, and 0/>∂∂ρp.  
- Implication: probability of default (and sovereign spread) is positive function of political risk and public debt levels, negative function of macroeconomic health.

### Empirical model specification
- Panel specification: ititiit uXY++=βα, i=1,....N; t=1,...T  (equation (8)), where Yit = logarithm of foreign currency bond spreads (annual averages); Xit = explanatory variables.  
- Estimators: fixed and random effects; Wu-Hausman test to choose; instrumental variables via 2-stage least squares and Generalized Method of Moments to address endogeneity/omitted variables.  
- Main explanatory blocks included in Xit:  
  - Solvency and liquidity: external reserves as percentage of GDP; inflation rate (logged); current account balance; economic growth.  
  - Global financial conditions: US policy interest rate (FED Funds); VIX stockmarket volatility index.  
  - Fiscal vulnerability: overall fiscal balance as share of GDP; public investment ratio to GDP.  
  - Political risk: PRI (principal component index combining World Bank governance and Heritage Foundation economic freedom indicators, centered on zero with positive values when political risk is low). Robustness: ICRG political risk variable and FRPRI (Ferrari and Rolfini) ranging between -2.5 (highest risk) and +2.5 (lowest risk). Sub-indexes: FRPOL (political violence), FRTRA (transfer), FREXP (expropriation). Political variables expected to have negative signs (higher political instability → higher spreads).

### Data
- Sample: spreads on 30 emerging market countries from EMBIG, period 1997-2007; annual spreads are period averages.  
- Macroeconomic variables: WEO database. Financial variables: Bloomberg. Fiscal variables: GFS database. Political risk variables: World Bank governance database and Heritage Foundation.  
- Note: 20 percent increase in the political risk index is equivalent to moving from the bottom quintile to the medium-risk range of the country distribution (textual definition).

### Estimation results (selected quantitative findings)
- Hausman test: rejected the fixed effects model at 1 percent significance level.  
- Table 3 (random effects estimates, dependent variable: Annual Mean Spread) — selected coefficients (robust standard errors in parentheses; significance * 10%, ** 5%, *** 1%):  
  - PRI: -0.168 (0.050)*** in column (1); -0.179 (0.052)*** in (2); -0.1575 (0.070)** in (3); -0.161 (0.06)*** in (4); -0.159 (0.013)*** in (5).  
  - Fiscal Balance: -7.76 (1.512)*** in (1); -7.83 (1.970)*** in (2); -4.297 (2.106)** in (3); -4.708 (2.05)** in (4); -5.59 (1.836)*** in (5).  
  - Public Investment: -0.054 (0.026)** in (1); -0.078 (0.025)*** in (2); -0.072 (0.032)** in (3); -0.065 (0.02)** in (4); -0.06 (0.026)** in (5).  
  - FED Funds Rate: -0.007 (0.030) in (1); -0.007 (0.031) in (2); -0.001 (0.032) in (3).  
  - Log inflation: 0.178 (0.082)** in (1); 0.177 (0.083)** in (2); 0.169 (0.085)** in (3).  
  - Reserves: -1.664 (0.875)** in (1); -2.15 (0.795)*** in (2); -2.34 (0.785)*** in (3).  
  - Current account balance: -1.28 (0.675)** in (1); -1.66 (0.61)*** in (2); -1.81 (0.606)*** in (3).  
  - TOT: -0.011 in (1); -0.010 in (2); -0.011 in (3) (standard errors and significance reported in table).  
- Sample sizes and fit: N = 188, 245, 173, 128 across columns (varies by specification); Overall R-Square = 0.21, 0.17, 0.27, 0.46 (column 4: full specification explains 46 percent of variation).  
- Interpretation and elasticities reported in text:  
  - "A 10 percent increase in our political risk index leads to a 10 basis point increase in spreads."  
  - "A 10 percent increase in the fiscal surplus reduces spreads by 2 percent, implying that one percent of GDP improvement in the primary balance can help decrease spreads by about 30-40 basis points."  
  - Public investment coefficient significant and negative, but the fiscal balance effect is several orders of magnitude larger; deficit-financed investment does not lower spreads.  
- Interaction effects (columns 5 and 6): slope dummies introduced for high market volatility (dummy = 1 if VIX > 25) and prior default history (dummy = 1 in year of default and subsequent years). Findings:  
  - Political factors do not matter more during periods of financial stress or in countries with prior default history (interaction terms with PRI insignificant).  
  - Fiscal balance matters more for countries with prior default or in high volatility: e.g., in countries with prior default, a 1 percent of GDP increase in the fiscal deficit would increase spreads by about 80 basis points (textual statement).

### Robustness analysis
- Methods: FGLS to account for heteroskedasticity across panels; IV using debt-to-GDP instrument for overall fiscal balance with 2SLS and GMM. Results: political and fiscal variables remain significant and robust.  
- Alternative solvency/liquidity/fiscal measures: higher real growth → lower spreads; high debt-to-GDP → higher spreads.  
- Political risk components (Table 5, random effects): effects on spreads when replacing PRI with Ferrari and Rolfini subcomponents (coefficients and R-Square reported):  
  - Rrexpr (expropriation): -0.52, R-Square 0.46, Obs 128 (standard error (0.25)** reported).  
  - Rrtra (transfer): -0.069, R-Square 0.33, Obs 128 (0.21).  
  - Rrpol (political violence): -0.22, R-Square 0.37, Obs 128 (0.26).  
  - PolRisk (ICRG-based): -0.038, R-Square 0.43, Obs 172 (0.01)***.  
- Key robustness conclusion: expropriation (creeping expropriation) appears most closely related to bond spreads; ICRG political risk variable also highly significant.

### Conclusions and policy implications
- Empirical findings (30 EMs, 1997-2007): political risk factors, including expropriation risk, significantly raise sovereign spreads; fiscal variables are more important with larger impact on spreads.  
- Fiscal health matters: high deficits or debt increase default risk and spreads. Increasing capital spending lowers spreads only if it does not widen the fiscal deficit.  
- Asymmetry: sensitivity of spreads to fiscal risk is larger for countries with previous defaults (reputational consequences).  
- Two policy implications emphasized:  
  - Fiscal prudence is crucial to reduce borrowing costs: country-specific fiscal health is important despite global financial conditions; markets punish underestimated fiscal risks via wider spreads, especially for countries with poor fiscal track records.  
  - Business climate and institutions (political stability) matter: poor political stability and weak institutions raise perceived country risk, reduce capital inflows, depress investment, and can lower economic growth.

*Source: IMF working paper content unit _wp08259 (Sections II–VII summary as provided).*

### REFERENCES

### _wp08259 - REFERENCES

### Sovereign spreads, emerging markets, and country risk
- Arora, V., and Cerisola, M. (2001) “How Does U.S. Monetary Policy Influence Sovereign Spreads in Emerging Markets” IMF Staff Papers, 48.  
- Asonuma, T. (2008) “Sovereign Default and Negotiation: Endogenous Recovery Rates, Interest Rate Spreads, and Credit Rating” mimeo.  
- Baldacci, E. (2007) “Beyond the Davos Consensus: A New Approach to Country Risk”, SACE Working Paper, 3.  
- Cavallo, E., and Valenzuela, P. (2007) “The Determinants of Corporate Risk in Emerging Markets: An Option-Adjusted Spread Analysis” Inter-American Development Bank Working Paper, 602.  
- Ciarlone, P., Piselli, P., and Trebeschi, G. (2007) “Emerging Market Spreads and Global Financial Conditions”, Temi di Discussione Banca d’Italia, 637.  
- Dailami, M., Masson, P., and Padou, J.J. (2005) “Global Monetary Conditions Versus Country Specific Factors in the Determination of Emerging Market Debt Spreads” World Bank Policy Research Working Papers, 3626.  
- Eaton, J., and Gersovitz, M. (1981) “Debt with Potential Repudiation: Theoretical and Empirical Analysis”, Review of Economic Studies, 74.  
- Eaoton, J., Gersovitz, M., and Stiglitz, J.E. (1986) “The Pure Theory of Country Risk”, National Bureau of Economic Research. Working Paper Series, No. 1894.  
- Eichengreen, B., and Mody, A. (1998) “What Explains Changing Spreads on Emerging Market Debt: Fundamentals or Market Sentiment”, National Bureau of Economic Research. Working Paper Series, No. 6408.  
- Ferrucci, G. (2003) “Empirical Determinants of Emerging Market Economies’ Sovereign Bond Spreads”, Bank of England Working Paper, 205.  
- Gibson, R., and Sundaresen, S.M. (1999) “A Model of Sovereign Borrowing and Sovereign Yield Spreads”, Paine WebberWorking Paper Series at Columbia University, EFA0044.  
- Gonzales-Rosada, M., and Levy-Yeyati, E. (2006) “ Global Factors and Emerging Market Spreads” Inter-American Development Bank Working Paper, 552.  
- Hartelius, K., Kashiwase, K., and Kodres, L. (2008) “Emerging Market Spread Compression: Is It Real or is it Liquitity?”, IMF Working Paper, WP/08/10.  
- Kamin, S.B., and von Kleinst, K. (1999) “The Evolution and Determinants of Emerging Market Credit Spreads in the 1990s” BIS Working Paper, 68.  
- McGuire, P., and Schrijvers, M.A. (2003) “Common Factors in Emerging Market Spreads” BIS Quarterly Review, December.  
- Min, H.G. (1998) “Determinants of Emerging Market Bond Spreads. Do Economic Fundamentals Matter?” World Bank Policy Research Working Paper, 1899.  
- Ozatay, F., Ozmen, E., and Sahinbeyoglu, G. (2007) “ Emerging Market Sovereign Spreads, Global Financial Conditions, and U.S. Macroeconomic News” Economic Research Center Working Papers in Economics, 7.  
- Rocha, K., and Garcia, F.A. (2006) “Term Structure of Sovereign Spreads in Emerging Markets. A Calibration Approach for Structural Models” mimeo.  
- Rowland, P., and Torres, J.L. (2004) “Determinants of Spread and Creditworthiness for Emerging Market Sovereign Debt: A Panel Data Study” Working Paper Banco de la Republica, Colombia.  
- Schularick, M. (2006) “Financial Globalization and Emerging Market Bond Price Bubbles: Some Historical Lessons”, mimeo.  
- Singh, M., and Andritky, J. (2005) “Overpricing in Emerging Market Credit-Default-Swap Contracts: Some Evidence from Recent Distress”, IMF Working Paper, WP/05/125.  
- Uribe, M., and Zue, V.Z. (2006) “Country Spreads and Emerging Countries: Who Drives Whom?” Journal of International Economics, 69.  
- Gonzales-Hermosillo, B. (2008) “Investors’ Risk Appetite and Global Financial Market Conditions”, IMF Working Paper, WP/08/85.  

### Political risk, elections, and fiscal policy
- Alesina, A., Cohen, G.D. and Roubini, N. (1992) “Macroeconomic Policies and Elections in OECD Democracies”, Economics and Politics, 4: 1-30.  
- AON (2007) “Political Risks: Nationalism Gaining Ground”, Risk Bulletin, February.  
- Buti, M. and Van den Noord, P. (2003) “Discretionary Fiscal Policy and Elections: The Experience of the Early Years of EMU”. OECD Economics Department Working Paper, ECO/WKP(2003)5.  
- Hallerberg, M. and Von Hagen, J. (1997) “Electoral Institutions, Cabinet Negotiations and Budget Deficits in the European Union (EU)”, CEPR Working Paper, 1555.  
- Hallerberg, M. and Wolff, G. (2008) “ Fiscal institutions, ficsal policy and sovereign risk premia in EMU”, Public Choice, p. 279-396.  
- Moser, C. (2007) “The Impact of Political Risk on Sovereign Bond Spreads. Evidence from Latin America”, mimeo.  
- Pantzalis, C., Stangeland, D., and Turtle, H. (2000) “Political Elections and the Resolution of Uncertainty: The International Evidence”, Journal of Banking and Finance, 24.  
- Pesaran, H., Shin, Y., and Smith, R. (1999) “Pooled Mean Group Estimator of Dynamic Heterogeneous Panels”, Journal of the American Statistical Association, 94.  
- Persson, T. and G. Tabellini. (1999) Political Economics and Public Finance. In A. Auerbach and M. Feldstein (Eds.). Handbook of Public Economics. Vol III. Amsterdam: North Holland.  
- Rodrick, D. (1991) “Policy Uncertainty and Private Investment in Developing Countries”, Journal of Development Economics, 36.  
- Roubini, N. and J.D Sachs. (1989) “Political and Economic Determinants of Budget Deficits in the Industrial Democracies”, European Economic Review, 33: 903-938.  
- Stein, E. and Streb, J. (2004) “Elections and the Timing of Devalutations”, Journal of Development Economics, 36.  
- Weingast, B., Shepsle, K. and Johnson, C. (1981) “The Political Economy of Benefits and Costs: A Neoclassical Approach to Redistributive Politics”, Journal of Political Economy, 89: 642-664.  
- WEF, (2007) Global Risks 2007. A Global Risk Network Report, World Economic Forum, Janauary.  

### Credit ratings, default models, and structural approaches
- Afonso, A. (2002) “Understanding the Determinants of Government Debt Ratings: Evidence for the Two Leading Agencies”, CISEP Working Paper, 2.  
- Afonso, A., Gomes, P., and Rother, P. (2007) “ What “Hides” Behind Sovereign Ratings?” ECB Working Paper, 711.  
- Cantor, R,, and Packard, F. (1996) “Determinants and Impacts of Sovereign Credit Rating”, The Journal of Fixed Income, 3.  
- Merton, R. (1974) “On the Pricing of Corporate Debt: The Risk Structure of Interest Rates”, Journal of Finance, 29.  
- Kulatika, N., and Marcus, A.J. (1987) “A Model of Strategic Default of Sovereign Debt”, Journal of Economic Dynamics and Control, 11.  
- Eaton, J., and Gersovitz, M. (1981) “Debt with Potential Repudiation: Theoretical and Empirical Analysis”, Review of Economic Studies, 74.  

### Global financial conditions, liquidity, and contagion
- Baldwin R. (2006) “Globalization: The Great Unbundling(s) ”, Prime Minister’s Office, Economic Council of Finland.  
- Dailami, M., Masson, P., and Padou, J.J. (2005) “Global Monetary Conditions Versus Country Specific Factors in the Determination of Emerging Market Debt Spreads” World Bank Policy Research Working Papers, 3626.  
- Eichengreen, B., and Leblang, D. (2006) “Democracy and Globalization, National Bureau of Economic Research”, National Bureau of Economic Research. Working Paper Series, No.12450.  
- Hartelius, K., Kashiwase, K., and Kodres, L. (2008) “Emerging Market Spread Compression: Is It Real or is it Liquitity?”, IMF Working Paper, WP/08/10.  
- International Monetary Fund (2008) Financial Stability Report,IMF, Washington, DC.  
- McGuire, P., and Schrijvers, M.A. (2003) “Common Factors in Emerging Market Spreads” BIS Quarterly Review, December.  
- Gonzales-Hermosillo, B. (2008) “Investors’ Risk Appetite and Global Financial Market Conditions”, IMF Working Paper, WP/08/85.  

### Empirical methods, calibration, and panel data techniques
- Blundell, R., and Bond, S. (1998) “Initial Conditions and Moment Restrictions in Dynamic Panel Data Models”, Journal of Econometrics, 87.  
- Ferrara, F., and Rolfini, R. (2008) “Investing in a Dangerous World: A New Political Risk Index”, SACE Working Paper, 6.  
- Giavazzi, F., Jappelli T., and Pagano M. (2000) “Searching for Non-Linear Effects of Fiscal Policy: Evidence from Industrial and Developing Countries”, National Bureau of Economic Research. Working Paper Series, No. 7460.  
- Faria, A., Mauro, P., Minnoni, M., and Zaklan, A. (2006) “The External Financing of Emerging Market Countries: Evidence from Two Waves of Financial Globalization”, IMF Working Paper, WP/06/205.  
- Ferrucci, G. (2003) “Empirical Determinants of Emerging Market Economies’ Sovereign Bond Spreads”, Bank of England Working Paper, 205.  
- Pesaran, H., Shin, Y., and Smith, R. (1999) “Pooled Mean Group Estimator of Dynamic Heterogeneous Panels”, Journal of the American Statistical Association, 94.  
- Rocha, K., and Garcia, F.A. (2006) “Term Structure of Sovereign Spreads in Emerging Markets. A Calibration Approach for Structural Models” mimeo.  
- Uribe, M., and Zue, V.Z. (2006) “Country Spreads and Emerging Countries: Who Drives Whom?” Journal of International Economics, 69.  

*Source: _wp08259 - REFERENCES*

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_Source: https://www.imf.org/-/media/websites/imf/imported-full-text-pdf/external/pubs/ft/wp/2008/_wp08259.pdf_