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Counting the investor vote: political business cycle effects on sovereign bond spreads in developing countries

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Abstract

International business research has paid scant attention to whether and how electoral politics and economic policies affect foreign investment risk assessment, particularly in developing countries, where the last decade has seen both considerable foreign investment and domestic progress toward democratization and electoral competitiveness. We respond with development and testing of a framework using partisan and opportunistic political business cycle (PBC) theory to predict the investment risk perceived by investors holding sovereign bonds during 19 presidential elections in 12 developing countries from 1994 to 2000. Consistent with our framework, we find that bondholders perceive higher (lower) investment risk in the form of higher (lower) credit spreads on their sovereign bonds as right-wing (left-wing) political incumbents appear more likely to be replaced by left-wing (right-wing) challengers. For international business research, our findings illustrate the promise of PBC theory in explaining the election-period behavior of sovereign bondholders and, perhaps, other investors who also ‘vote’ in developing country elections and can substantially influence the price and availability of capital there. For developing country investors and states, our findings highlight the financial effects of democracy in action, and underscore the importance of state communication with investors during election periods.

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Notes

  1. Descriptions of right-wing vs left-wing supporters in Hibbs (1977) and others (e.g., Berlemann and Markwardt, 2003) include a progressive tax system and, thus, the possibility that right-wing supporters with considerable assets of a nominally fixed value will suffer from faster progression through higher tax brackets as inflation increases. This description of right-wing supporters seems particularly well suited to the empirical context of this study and also to agencies and their assessments of developing country economic policies for their impact on the interests of investors holding sovereign bonds with nominally fixed coupon amounts.

  2. By ‘final election day’ we mean the polling date or dates of the general election or, in the case of multiple electoral rounds, the polling date or dates of the run-off general election. For the remainder of this study, we use the term ‘election day’ to refer to this final general election-day concept.

  3. Trends in the stock of debt securities issued abroad roughly mirror trends in cumulative FDI flows into these countries over the same period. Cumulative FDI inflows to the Philippines from 1994 to 2000 were approximately $9.9 billion. Cumulative FDI inflows to Mexico from 1994 to 2000 were approximately $81.1 billion. Cumulative FDI inflows to Argentina from 1994 to 2000 were approximately $68.3 billion.

  4. Lamy and Thompson (1988) suggest that relative spreads are a more stable risk measure than absolute spreads, especially where the general level of interest rates fluctuates substantially. Consistent with this approach, we define spreads on a foreign sovereign bond relative to comparable US Treasuries: (Yield Foreign −Yield US )/Yield US .

  5. We thus integrate prior PBC theories, which in their original formulations make contradictory characterizations of incumbents (e.g., they are identical and non-ideological in opportunistic PBC theory, and have distinct policy preferences in partisan PBC theory).

  6. Alternatively, one could conceive of a situation in which an incumbent, certain of defeat, would deem it futile to engage in pre-election spending sprees to buy votes. This scenario, however, contradicts both theoretical and empirical work on opportunistic political business cycles (e.g., Schultz, 1995; Alesina et al, 1997b). This remains an interesting question for future research, and the authors thank an anonymous referee for the suggestion.

  7. Other researchers estimate absolute spreads (e.g., Larraìn et al., 1997, which then requires the addition of a right-hand side control, usually measured as the daily observed yield on actual or synthetic US Treasuries of similar maturity.

  8. Moody's Investor Service and other major credit rating agencies (e.g., Standard & Poor's Rating Services) typically use 17 ordinal levels to assess the risk of default by sovereigns: Aaa=16; Aa1=15; Aa2=14; Aa3=13; A1=12; A2=11; A3=10; Baa1=9; Baa2=8; Baa3=7; Ba1=6; Ba2=5; Ba3=4; B1=3; B2=2; B3=1; and C=0. Ratings below Baa3 are considered to be non-investment ‘junk’ grade. The value of maintaining an investment grade sovereign rating is discussed in White (2001).

  9. A financial crisis is defined using a measure developed by Frankel and Rose (1996), who define one type of financial crisis in a country – a currency crisis – as a depreciation of 20% or more in the nominal exchange rate of a country's currency against the US dollar in a given year. Where there are consecutive years of such depreciation, they impose the additional condition that each additional consecutive year of depreciation be at least 10% more than the previous year's depreciation.

  10. This specification of the expectations dummy imposes symmetry on the magnitude of positive and negative effects resulting from elections. This approach is consistent with previous PBC empirical research (Alesina et al., 1997b). As an additional check, we implement an F-test comparing our spreads model with this symmetry restriction to an alternative spreads model without this restriction – that is, separate dummies for high and low expectations of right-wing victory. At any commonly acceptable significance levels, we fail to reject the null hypothesis of symmetry in the restricted model, a result consistent with our more parsimonious model choice.

  11. A recent working paper by Berlemann and Markwardt (2003) illustrates, again, the paucity of comparable pre-election polling data. They find cross-country polling data based on comparable sampling procedures, polling questions and statistical analyses for post-World War II elections in only six OECD countries.

  12. H1 above is the reduced form of the following inequality: β 1+β 3+β 4+β 5<β 1+β 3<β 1+β 3−β 4−β 5.

  13. H2a above is the reduced form of the following inequality: β 1−β 4<β 1<β 1+β 4, whereas H2b is the reduced form of the opposite inequality: β 1−β 4>β 1>β 1+β 4.

  14. Parties are placed in a fourth classification as ‘other’ if both name-based and commentator-based criteria cannot clearly classify them into left wing, right wing, or centrist. Where an incumbent party in our sample is classified as ‘other’ by the DPI – and there were only three such instances – we consulted IFES and Polisci.com for additional information on which to make a judgment of left- vs right-wing party orientation.

  15. We also checked for the stationarity of bond spread observations for the 12 different bond series from which the sample was drawn. Using Dickey–Fuller (1979) and Phillips–Perron (1988) tests, we were able to reject the null hypothesis of non-stationarity for five of 12 bond series at the 1% level, for eight of 12 bond series at the 5% level and for 10 of 12 bond series at approximately the 10% level. We could not reject the null hypothesis for the Polish PDIB series and the Russian IV series bonds at commonly acceptable levels of significance. Results excluding these last two bonds are consistent in signs and significance with those reported below, and are available from the authors.

  16. One cell in the PBC framework, IV, left-wing incumbents in close-call elections (GovRbegin=0, λD med=0), is empty when using a victory margin less than 3% to define a close call. Pre-election bond spread trends are therefore simulated for this scenario. When we redefine a close call more to include elections with victory margins less than 5% or less than 10%, this cell of the PBC framework is no longer empty. Using these alternative definitions of close call, we obtain completely consistent slope estimates. These results are available from the authors.

  17. Gross outliers excluded from GEEs leading to these test results varied from approximately 5% of the sample with the 60-day sample and convergent bondholder expectations to nearly 23% of the sample with the 90-day sample and constant bondholder expectations. In all four weighted GEEs, excluded gross outliers were distributed across six elections: Argentina 1995, 1999; Brazil, 1994; Mexico, 2000; Russia, 2000; and Venezuela, 1998.

  18. Indeed, slopes for pre-election spreads in five of six possible cases in Table 3 exhibit negative point estimates of varying magnitude. This generally negative trend in the run-up to polling is consistent with the downward-sloping trend in pre-election slopes that Block and Vaaler (2004) observed. They connected this trend to a larger pre-election spreads ‘bubble’ phenomenon extending over a six-month period: From approximately 180 to 90 days before elections, spreads on several developing country sovereign bonds increased, only to decrease substantially in the final run-up to polling. The resulting ‘bubble’ was interpreted as a temporary risk premium on developing country debt associated with rising and then declining uncertainty about electoral outcomes and the extent of opportunistic behavior by incumbents. Recurring negative trends here, however, have a different interpretation given our framework: as uncertainty regarding electoral outcomes is resolved in the final run-up to polling, steeper or shallower (or in one case slightly positive) spreads slopes reflect bondholder consideration of both opportunistic and partisan effects.

  19. Specifically, median regression fits medians to a linear function of covariates (in contrast to OLS, which fits means). This estimator ‘…is potentially attractive for the same reason that the median may be a better measure of location than the mean’ (Buchinsky, 1998: 89). The median estimator of θ solves

    where m(x i , θ) is the conditional median of y given x. Median estimates include all observations without explicit weighting, yet median estimates are not sensitive to dependent variable outliers. We still prefer the weighted GEE approach to the median regression approach because of flexibility. Median regression does not provide the flexibility to deal with other panel data estimation adjustments related to clustering, cross-sectional heteroskedasticity, or serial correlation. The weighted GEE does, and thus remains our preferred estimator for our data.

  20. Results from these alternative model specifications and estimations are available from the authors.

  21. At 90 days before the election, the yield on Argentina's series FRB sovereign bond maturing in March 2003 stood at 22.16%, whereas US Treasuries of comparable maturity yielded 7.41%, implying a relative spread of approximately 1.99. Based on the weighted GEE analysis using a 90-day pre-election window (Table 3, Column 2), we predict for elections with a right-wing incumbent and a high constant likelihood of re-election (λD hi) a slope coefficient of −0.00139 (β 1+β 3+β 4+β 5). Over a 90-day period, relative spreads are predicted to decrease by approximately −0.1251 (−0.00139 × 90=−0.1251). This implies a decrease in relative spreads from 1.99 to 1.76, or a decrease in the yield on the Argentine sovereign bond from 22.16 to 20.45%, assuming no change in the relevant US Treasury yield.

  22. Interestingly, spreads on the Polish bond are lower on average than on the Argentine bond, even though the Polish government is left wing and the Argentine government is right wing, and both are expected to be re-elected. This oddity reminds us that credit risk is a function of many different factors including, but not limited to, PBC considerations.

  23. See previous note. At 90 days prior to the 2000 presidential election, Poland's Series PDIB sovereign bond, maturing in December 2017, yielded 8.18%, whereas yields on US Treasuries of comparable maturity stood at 6.20%. On election day, the yield on this Polish sovereign bond had increased to 8.48%.

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Acknowledgements

We thank Isaac Fox, Laurent Jacque, Michael Klein, Frank Linden, Gerry McNamara, Tom Murtha, Mike Sher, Journal of International Business Studies Department Editor Lorraine Eden and, especially, three anonymous JIBS reviewers for helpful comments, criticisms and suggestions on earlier drafts of this paper. This research also benefited from seminar presentations at the Brandeis International Business School and the Humphrey School of Public Policy at the University of Minnesota. We gratefully acknowledge financial support for this research from the Fletcher School of Law and Diplomacy Academic Dean's Office, and from the Fletcher School of Law and Diplomacy's Hitachi Center for Technology and International Affairs.

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  1. The Fletcher School of Law and Diplomacy, Tufts University, Medford, MA, USA

    Paul M Vaaler & Steven A Block

  2. Singapore Management University, Singapore

    Burkhard N Schrage

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  1. Paul M Vaaler
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Correspondence to Paul M Vaaler.

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Accepted by Lorraine Eden, Depatmental Editor, 3 July 2004. This paper has been with the author for two revisions.

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Vaaler, P., Schrage, B. & Block, S. Counting the investor vote: political business cycle effects on sovereign bond spreads in developing countries. J Int Bus Stud 36, 62–88 (2005). https://doi.org/10.1057/palgrave.jibs.8400111

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