categories, creditworthiness and contagion · market pressures than developed ones. •also have...

Categories, Creditworthiness and Contagion

Sarah Brooks, Ohio State University

Raphael da Cunha, Ohio State University

Layna Mosley, University of North Carolina

How Investors’ Shortcuts Affect Sovereign Debt Markets

International Political Economy Society, Nov. 9, 2012

Assessing Sovereign Risk?

• When setting risk premiums for sovereign debt, at what do investors look?

• If governments are attentive to market pressures, how do these pressures operate?

• Investors’ primary concerns are currency, inflation and default risk.

• 1990s and 2000s: investors treated developed and emerging market countries differently.

• Assumed no default risk among developed nations, so consider only macro-indicators (deficits, inflation)

• Worried more about default among developing nations, so looked also at supply side policies, government ideology, elections.

Assessing Sovereign Risk • Developing nations are therefore more constrained by

market pressures than developed ones.

• Also have greater need to attract foreign capital.

• And are more exposed to externally-induced volatility:

• Importance of push vs. pull factors to risk premiums.

• Commodity exporters

• The borrowing strategies pursued by emerging market governments can exacerbate “ability to pay” concerns.

• After accounting for policy outcomes, emerging and frontier market countries pay higher risk premiums than developed nation borrowers.

Variation in Market Constraints

• The prices governments pay to borrow on international markets vary markedly: • Across countries (sovereign credit ratings, macroeconomic

fundamentals)

• Over time (liquidity, risk appetite, elections) (Archer et al 2007; Bernhard and Leblang 2006; Cantor and Packer 1996; Hardie 2006; Jensen and Schmith 2005; Mosley 2003; Tomz 2007)

• In addition, different types of governments are differently constrained by global capital markets: developed vs. developing

commodity vs. manufacturing exporters

borrowers from commercial banks vs. bond markets (Campello 2012, Mosley 2003, Kaplan 2012, Wibbels 2006)

Are market constraints interdependent?

• Does the sovereign risk premium paid by one country systematically shape the way that investors assess sovereign risk in other nations?

• If so, how, and through which channels do sovereign risk assessments diffuse?

• One principal mechanism: country classifications

• Professional investors sort countries into “peer” groups

Are market constraints interdependent? • Optimal portfolio diversification dictates that professional

investors often manage highly dissimilar assets

• sovereign debt, corporate debt, equities, derivatives and cash

• and they often invest in a diverse range of locations

• They rely on information shortcuts to assess risk (heuristics)

• Summary indicators of fiscal and monetary outcomes.

• Budget deficit

• Debt ratios

• Inflation

• Also: categories

• “developed” vs. “developing” (Mosley 2003)

• peripheral Europe: “emerging Europe” in the 1990s “eurozone” in the 2000s “PIIGS” in the 2010s

Sovereign Peer Groupings

• Investors may over- or under-estimate sovereign risk based on the category into which the country is grouped:

• When investors are more optimistic about a given group of countries, each country in that group will experience an improvement in market access.

• When investors are more pessimistic about a category of countries, a borrower within that category may suffer – even if the country’s fundamentals do not warrant such pessimism.

• This implies that investors’ responses to domestic policy are neither fixed, nor fully objective.

Interdependent Sovereign Risk

• Over the long term, sovereign risk assessments should vary with domestic fundamentals.

• In the short term, sovereign risk may correlate across nations due to contagion from crises or changes in global liquidity.

• But, even after controlling for these short- and long-term effects, we expect an additional effect of “country category”

• Country risk premium will be significantly correlated with the risk premiums paid by other borrowers in the same category.

(Hypothesis 1)

Comparing Countries

• We also expect that, when investors evaluate individual sovereign borrowers, they do so in relative terms:

• The risk premium associated with a given fiscal deficit, for instance, depends on what other countries are doing.

• Governments are evaluated relative to what they are expected to do.

• Tomz 2007: stalwarts vs. lemons

• Here, peer categorizations matter because they define the relevant comparison group.

• Sovereign risk premiums are associated, all else equal, with what other borrowers in the same category are doing, in terms of government budgets, and deficits. (Hypothesis 2)

Data and Method

• Dependent variables: • Sovereign spreads (EMBI): monthly and annual data for 26

emerging market economies, 2001-2010.

• Credit default swap (CDS) prices, monthly data for 26 developed and developing countries, 2000-2010.

• Independent variables: • Domestic economic: government debt, government consumption,

budget balance, inflation, capital account openness.

• Domestic political: democracy, government ideology, opposition party ideology, electoral cycle, presidential/parliamentary

• Global: US interest rate, US treasury bond yields, US stock market returns.

• Peer group

Which Peer Groups Matter?

• We examine 3 types of investment categorizations:

1. Region:

• Asia, Western Europe, post-Communist Europe, Latin America, Non-Latin Caribbean, Middle East and North Africa, North America, South Asia, and Africa [World Bank categories]

2. Market and Economic Development:

a. MSCI: Emerging Markets; Frontier; Developed

b. FTSE: Emerging Markets; Frontier; Developed; Advanced Emerging; Secondary Emerging

3. Risk Rating:

• Fitch Long-Term Sovereign Credit Ratings

• (Coded as a 1-12 sovereign risk score)

Data and Method

• We estimate cross-sectional time series models, using an Error Correction Model (ECM).

• This allows us to consider both the short-term and long-term effects of the regressors.

• Generalized least squares estimator, country fixed effects, linear time trend.

• Full results of the estimations are available in the paper (Tables 1 through 5)

Main Findings

Main Findings

• In terms of relative assessments (Hypothesis 2): • The level of government debt in (regional) peer countries is

negatively and significantly associated with spreads.

• A country’s own debt level is, as we would expect, positively and significantly associated with spreads.

• Categorization may provide governments with an opportunity to outperform their peers, for which they are rewarded.

• If we take sovereign ratings as the dependent variable,

• When one’s rating category peers have better fiscal outcomes, one’s rating is higher, all else equal.

• Again, a country’s own fiscal balance also is positively and significantly associated with one’s sovereign rating.

Caveats and Conclusion • Annual data obscures what are often shorter-term movements in

sovereign debt markets.

• Models suggest that almost all of the disturbances to equilibrium in risk premiums are corrected within one year.

• Most of the political variables included in our models, however, are measured on an annual basis.

• Sample: a limited set of countries (e.g. those for which there is a CDS market or which are included in EMBI+)

• More generally, aggregate-level observational data may not be the best way to assess our proposed causal mechanisms.

• Future work: survey experiment design.

• Our findings suggest, however, that the ways in which countries are grouped – and changes in those groupings – may be important determinants of governments’ capacity to access bond markets.

DV: Annual Δ_Spread Table 1. Explaining Annual Changes in Sovereign Debt Spreads

Peer Category:

1 2 3 4

Coef. Std. Err. Coef. Std. Err. Coef. Std. Err. Coef. Std. Err.

Spread t-1 -1.08 *** 0.07 -1.12 *** 0.06 -0.94 *** 0.07 -1.11 *** 0.07

Peer Diffusion

Peer Spread

t-1 0.21 ** 0.10 -0.20 * 0.11 0.22 * 0.13 -0.26 *** 0.09

Δ 0.37 *** 0.07 0.09 0.07 0.45 *** 0.10 -0.13 0.09

Domestic Politics and Economy

Gov Consumption

t-1 1.02 24.23 4.59 27.13 3.72 24.43 19.76 25.89

Δ -23.86 19.78 -4.07 21.34 -15.16 20.08 -36.84 * 22.33

Debt

t-1 4.37 ** 2.18 4.15 ** 1.88 2.77 2.24 5.51 *** 2.10

Δ 6.40 *** 2.26 5.78 *** 1.76 7.04 *** 2.13 7.88 *** 2.15

Maturity

t-1 1.15 5.10 -3.85 5.46 -7.16 5.38 -2.40 4.82

Δ -1.79 3.56 -6.35 * 3.62 -8.14 ** 3.66 -2.77 3.51

Inflation

t-1 0.33 0.46 0.07 0.48 0.68 0.46 0.63 0.52

Δ 0.02 0.33 -0.11 0.34 0.10 0.34 0.02 0.39

Budget Balance

t-1 -20.89 ** 10.57 -26.37 ** 10.98 -16.42 11.20 -20.98 * 11.21

Δ -31.89 *** 8.30 -25.73 *** 8.47 -25.46 *** 8.64 -23.93 *** 8.79

Region Risk Rating MSCI FTSE


Peer Category:

1 2 3 4


Democracy

t-1 11.86 14.17 20.07 14.42 12.47 13.52 15.10 12.90

Δ 22.40 22.37 25.12 21.99 5.68 23.53 32.87 22.03

KA Open

t-1 -80.68 ** 33.55 -65.33 * 35.37 -54.40 33.85 -59.09 * 33.26

Δ -59.39 * 36.41 -56.40 40.39 -58.81 40.33 -31.58 35.59

Years to Election

t-1 -32.76 ** 14.63 -29.64 * 15.49 -25.99 * 14.44 -25.52 ** 13.04

Δ -9.47 9.92 -12.17 9.98 -10.52 9.90 -7.66 8.88

Left

t-1 128.18 267.97 26.77 385.25 -30.57 440.41 28.30 337.53

Right

t-1 36.95 400.40 -673.79 * 399.72 -642.29 * 377.14 -650.50 * 346.34

Opposition Right

t-1 85.90 61.58 40.49 61.68 56.35 57.26 50.99 45.05

Opposition Left

t-1 116.75 * 70.25 104.07 68.31 93.53 67.58 54.50 55.99

System

t-1 -52.33 39.09 -7.75 39.86 1.05 39.45 -29.78 39.05

Risk Rating MSCI FTSERegion


Peer Category:

1 2 3 4


Common Shocks

US Prime Rate

t-1 29.75 ** 12.28 30.99 ***12.44 34.93 ***13.21 33.09 ***13.00

Δ -25.89 * 14.80 -68.22 ***14.88 -10.85 17.29 -70.54 ***15.19

Time

t-1 -12.85 8.95 -22.22 ***8.47 -9.43 9.64 -19.05 ** 8.42

Const. 25956 17988 44910 ***16975 19192 19351 38372 ** 16896

N. obs 171 171 171 171

Wald chi2

454.59 1353.14 479.67 444.68

Prob > chi2

0 0 0 0

FGLS error correction model of annual change in Sovereign Stripped Spreads *** p<.01; ** p<.05; * p<.1

Risk Rating MSCI FTSERegion

DV: Monthly Δ_CDS 1 2 3 4

Peer Category:


CDS

t-1 -0.11 *** 0.02 -0.13 *** 0.02 -0.09 *** 0.02 -0.09 *** 0.02

Peer Diffusion

Peer CDS

t-1 0.01 0.02 0.04 ** 0.02 -0.02 0.02 0.00 0.02

Δ 0.35 *** 0.05 0.17 *** 0.02 0.05 0.03 0.15 *** 0.05

Domestic Politics and Economy

Debt

t-1 0.67 ** 0.31 0.76 *** 0.26 1.19 ** 0.51 1.29 ** 0.66

Budget Balance

t-1 -0.36 1.30 -0.10 1.15 0.24 1.27 0.20 1.65

Inflation

t-1 0.25 0.92 0.14 0.83 -0.04 1.03 0.49 1.26

GDP per cap

t-1 0.01 0.02 0.02 * 0.01 0.01 0.01 0.00 0.02

KA Open

t-1 -6.65 4.68 -6.71 * 3.89 -7.16 4.82 -9.95 7.29

FX Rate

t-1 433 *** 121 397 *** 92 436 *** 95 444 *** 121

Δ 282 *** 79 324 *** 61 373 *** 64 363 *** 80

Democracy

t-1 -0.42 1.00 -0.51 0.83 -0.05 0.69 0.49 1.25

System

t-1 -7.08 20.55 -19.48 18.17 81.76 *** 15.26 63.29 48.74

Right

t-1 41.33 71.19 66.72 66.49 -193.06 *** 39.27 162.77 101.24

Region Risk Rating FTSE MSCI

DV: Monthly Δ_CDS 1 2 3 4

Peer Category:


Common Shocks

US Prime Rate

t-1 -1.08 1.60 -1.10 1.34 -1.01 1.57 -0.69 2.06

Δ -16.23 11.05 -16.66 * 9.24 -23.56 ** 9.68 -26.17 ** 13.07

US Stock Market

t-1 -2.89 *** 0.83 -3.14 *** 0.69 -3.41 *** 0.73 -2.85 *** 1.01

Δ -2.78 *** 0.48 -3.16 *** 0.39 -3.39 *** 0.40 -2.88 *** 0.59

Invest.Grade Yield

t-1 -5.94 6.37 -3.71 5.32 -3.83 5.36 -2.99 7.29

High Yield

t-1 -10.35 ** 4.87 -6.88 * 4.09 -11.77 *** 4.21 -7.56 5.59

Treasury Yield

t-1 -7.57 10.05 -6.90 8.33 -10.96 8.25 -9.63 11.15

Equity Premium

t-1 390.49 695.81 542.11 578.83 912.63 594.56 388.26 752.01

Volatility Premium

t-1 -0.02 0.39 0.26 0.32 0.65 ** 0.32 0.60 0.43

Term Premium

t-1 1.38 2.35 1.87 1.92 2.80 1.93 3.03 2.58

Stock Flows

t-1 -37.47 33.83 -49.66 * 28.94 -77.57 *** 31.33 -96.90 ** 41.74

Δ -45.32 ** 21.52 -43.38 ** 18.56 -67.72 *** 19.88 -85.81 *** 26.10

Bond Flows

t-1 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Δ 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Time -0.15 0.20 -0.19 0.17 0.10 0.23 0.18 0.31

Const. -4.41 62.70 -28.44 53.87 -93.90 * 53.93 -236.29 157.31

N. obs 927 1009 825 885

Wald chi2

443.44 556.07 536.41 368.31

Prob > chi2

0 0 0 0

FGLS error correction model of monthly change in CDS prices *** p<.01; ** p<.05; * p<.1


DV: Monthly Δ_Spreads 1 2 3 4

Peer Category:


Spread

t-1 -0.12 *** 0.02 -0.13 *** 0.02 -0.10 *** 0.01 -0.10 *** 0.02

Peer Diffusion

Peer Spread

t-1 0.06 *** 0.02 0.06 *** 0.02 0.00 0.02 0.02 0.02

Δ 0.51 *** 0.04 0.29 *** 0.03 0.34 *** 0.07 0.30 *** 0.04


FX Rate

t-1 414.73 *** 92.13 432.40 *** 77.88 394.42 *** 74.78 402.16 *** 84.45

Δ 1.56 62.82 58.09 54.88 46.95 53.33 40.06 58.30

DV: Monthly Δ_Spreads 1 2 3 4

Peer Category:


Common Shocks

US Prime Rate

t-1 -0.61 1.26 -2.50 ** 1.17 -2.66 ** 1.21 -2.00 1.38

Δ -7.41 9.22 -12.61 8.20 -17.93 ** 9.11 -16.53 * 10.14

Stock Flows

t-1 -60.41 ** 30.56 -63.23 ** 28.11 -81.70 *** 30.04 -78.15 ** 32.94

Δ -3.83 20.65 8.29 19.22 14.57 20.58 12.43 21.86

US Market

t-1 -1.41 ** 0.68 -2.31 *** 0.56 -2.00 *** 0.74 -2.03 *** 0.77

Δ 0.68 * 0.37 0.34 0.35 0.63 * 0.36 0.54 0.40

Invest.Grade Yield

t-1 10.13 * 5.95 9.63 * 5.39 5.78 5.72 15.16 *** 6.06

High Yield

t-1 5.22 4.51 10.74 *** 4.06 6.04 4.28 13.88 *** 4.57

Treasury Yield

t-1 -5.15 8.80 -4.12 7.98 -7.21 8.39 -8.38 9.15

Equity Premium

t-1 -1584 ** 666 -1968 *** 562 -2031 *** 579 -1893 *** 645

Risk Rating FTSE MSCIRegion

categories, creditworthiness and contagion · market pressures than developed ones. •also have...

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