Abstract
Most sovereign defaults are partial, with heterogeneous post-default outcomes, and commodity prices are an important determinant of sovereign default and the subsequent restructurings. In the case of emerging countries, as a result of direct dependence of government on revenues from commodity exports, declines in commodity prices reduce government’s resources to service the external debt thereby increase the chances of default. In this paper, we construct a country-specific commodity price index with time-varying weights based on commodity exports to quantify the impact of commodity prices on the partial default rate measured by debt arrears. We show that declines in commodity prices have a significant, positive effect on the default rate. The overall predicted effects for a one-standard deviation decrease in a composite of the level and change of the price index at its 1st, 2nd, and 3rd quartile, on average, are 14.2, 12.5, and 9.3 percentage points respectively. We also show that for a country-specific one-standard deviation decrease in the composite price index, the predicted effect varies from insignificant to an increase of 33.8 percentage points. The country-specific effect on the default rate generally increases in magnitude with a country’s dependence on commodity exports, while it depends heterogeneously on external indebtedness—increasing in magnitude for low levels (below a threshold of about 30 percent) of debt and decreasing thereafter.
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When it comes to analyzing the role of commodity prices for sovereign default, the common approach in the literature has been an indirect one that focuses on the role of terms-of-trade. In our view, there are two reasons for this choice. First, compared to commodity prices, terms-of-trade are a more broad-based measure of country’s ability to pay and thus deserve to be analyzed in their own right as a determinant of the sovereign default risk. Second, it is well known that, in the case of most emerging countries, terms-of-trade are driven, to a great extent, by trends in world prices. Therefore, for these countries, in the absence of the availability of a country-specific commodity price index, terms-of-trade may be considered as a useful proxy for commodity prices.
We use the IMF definition for emerging countries, in line with our approach of constructing the price index which is based on IMF (2009). The countries included in our sample, which are in Africa, the Americas, Asia, Eastern Europe, and the Middle East, are those that have full information available of the external public debt arrears for all years up to 2013. Because of the missing information of the external public debt arrears, Chile, as a well-known commodity exporter with default history, is not included.
In the related literature in commodity prices and sovereign default, Reinhart et al. (2016) also apply a fractional response model to predict the share of countries entering default.
Our main results continue to hold with no significant differences under a series of robustness tests, including the analysis of the impacts from default history, international reserves, and dropping no/low default countries.
Chen et al. (2010) show that “commodity currency” exchange rates have surprisingly robust power in predicting world commodity prices but the reverse relationship that commodity prices forecast exchange rates to be notably less robust. This is due to that, in contrast to the current exchange rate, the world price dynamics are driven mostly by global supply and demand conditions, which are typically quite inelastic. Thus, world commodity prices can serve as an exogenous shock to most commodity exporters. Hilscher and Nosbusch (2010) also state that an export-weighted price index, which uses time-varying weights of major commodities traded in world market, is plausibly exogenous.
Our procedure for constructing the price index, from a methodology perspective, is relevant to the literature that has developed and used price indices to analyze the implications of commodity prices for various macroeconomic outcomes, in general, not just for sovereign default (Arezki and Brückner, 2012; Fernandez et al., 2017, 2018). Hilscher and Nosbusch (2010) investigate the impact of the volatility of economic fundamentals on sovereign yield spreads and construct an export-weighted price index using time-varying weights with the prices of 12 major commodities to eliminate the endogeneity of their terms-of-trade measure, which is a work closely-related to ours. Our price index, by using country-specific, time-varying weights and focusing on the implications of price shocks for commodity exports on sovereign default risk, extends and contributes to this strand of literature as discussed in more detail in Sect. 2.
Easton and Rockerbie (1999) define the default as the occurrence of accumulated arrears on principal and interest payments at any time, rather than the standard definition in which a default is identified with the occurrence of a rescheduling of principal payments (Benjamin and Wright, 2013; Borensztein and Panizza, 2009; Detragiache and Spilimbergo, 2001). See Eq. (1) in Sect. 2.
Asonuma and Trebesch (2016) define post-default restructurings as the cases, in which payments are missed unilaterally and without the agreement of creditor representatives (unilateral default prior to negotiations). According to their coding, post-default restructurings account for around two thirds (111 out of 179) of all sovereign debt exchanges since 1978, and they are quite frequent like the occurrence of partial default as measured by the definition of Easton and Rockerbie (1999). See Table 1. Statistics of Partial Default Rate (1970–2013).
For example, Baldacci et al. (2011) investigate the (fiscal and political) determinants of sovereign bond spreads in a panel of 46 emerging economies over 1997–2008, showing a negative relationship between the level of terms-of-trade and spreads. Maltritz (2012) analyzes the determinants of sovereign yield spreads of 10 European Monetary Union members over the period 1999–2009 and reaches a similar conclusion. In a panel of 31 emerging economies over 1994–2007, Hilscher and Nosbusch (2010) show that both the change in terms-of-trade as well as its volatility are important predictors of EMBI spreads. Aizenman et al. (2013) find that CDS spreads consistently decrease with increase in the changes in Goldman Sachs Commodity Index (GSCI) and oil price in a panel of European Union countries over 2005–2012. Similarly, Zinna (2013) assesses the relationship between an emerging markets risk measure and both the level and the change of GSCI. There is also a literature studying the impact of terms-of-trade volatility on sovereign risk premia (see Aizenman et al., 2016; Catão and Kapur, 2006; Catão and Sutton, 2002).
By using the partial default rate as the dependent variable, our paper also complements the emerging theoretical/quantitative literature that examines the partial default mechanism (Arellano et al., 2023; Atolia and Feng, 2019; Aguiar et al., 2013, 2014; Alfaro and Kanczuk, 2009; Dubey et al., 2005).
There is also a strand literature that looks at the heterogeneity in terms of preemptive or “voluntary” vs. post-default restructurings. See Asonuma and Trebesch (2016) and Hatchondo et al. (2014). Also see Asonuma et al. (2020), Asonuma et al. (2016), and Sturzenegger and Zettelmeyer (2006) for additional empirical analysis.
Online Appendices contain more details of the data and of some of the results of empirical analysis.
The data on PPG external debt, including debt arrears and service, comes from the World Development Indicator (WDI), part of World Bank Open data, ranging from 1970 to 2013 annually, with shorter periods for some countries.
We select, and group homogeneous commodities based on the SITC division. For example, soybean oil and peanut oil, and iron ore and copper ore are grouped into the same elementary aggregates, respectively.
Besides satisfying the above criteria, commodities selected for constructing elementary aggregates in our paper satisfy the following requirements as well: they are representative of all commodities within the elementary aggregates with large enough global transaction volumes and remain on the market for some time to reduce disappearing and replacement situations.
See the online Appendix A, Table A.2: The Category Structure of Global Economic Monitor (GEM) Commodities Database as Presented in the Commodity Price Data (a.k.a. Pink Sheet)
There are five basic tests of the axiomatic approach: proportionality test, changes of units of measurement test, time reversal test, transitivity test, and allowing for substitution test. The Carli index fails the time reversal, transitivity, and allowing for substitution tests. The Dutot index fails changes of units of measurement and allowing for substitution tests. The Jevons index, on the other hand, passes all the tests (IMF, 2009, Table 10.2).
The economic approach requires a specific sample design involving quantities or value shares to translate a sample unweighted elementary index into an estimator of a weighted overall index and needs a check as to whether this estimated weighted index is an appropriate target, that is, one based on the behavioral assumptions of the enterprises or households responsible for exporting or importing the commodities. In other words, by taking account of the interdependence between prices and quantities and by making necessary behavioral assumptions of exporter/importer, the economic approach aims to estimate an “ideal” or “true” economic index for the elementary aggregates.
Agarwal et al. (2020)’s country-specific commodity net export price index (Gruss, 2014) is calculated based on 45 commodities and their predetermined 3-year average weights. Fernandez et al. (2018) create country-specific commodity price measures for Brazil, Chile, Colombia, and Peru over 1980–2014 with the information of 44 commodities’ prices, using constant weights (averages of 1999–2004 period) in the price index for various commodity groups, which is a reasonable assumption for estimation and analysis over the period 1980–2014. Fernandez et al. (2017) use data from World Bank’s Pink Sheet to construct three separate world commodity price indices for the cyclical components of Fuel, Agriculture, and Metal and Minerals, deflated using the US CPI. These indices are average prices of representative individual commodities weighted by world shares. Chen and Lee (2018)’s price index is defined as the world nominal prices of a country’s major commodity exports, which is deflated by the price index of the manufactured exports of all industrial economies. Ricci et al. (2013)’s commodity price-based terms-of-trade is constructed from the prices of six commodity categories (Food, Fuels, Agricultural Raw Materials, Metals, Gold, and Beverages) and measured against the manufacturing unit value index of the WEO database. It is weighted by the time-average (1980–2001) of export and import shares of each commodity category, defined in SITC II, in the total trade. Arezki and Brückner (2012) create a country-specific commodity export price index with time-invariant value of exported commodities (aluminum, beef, coffee, cocoa, copper, cotton, gold, iron, maize, oil, rice, rubber, sugar, tea, tobacco, wheat, and wood) in the GDP.
The FRM for cross-sectional observations is an extension of the general linear model. It provides an alternative approach for dealing with the variables bounded at both extremes where observations “pile-up” at one of the extreme points. In particular, it ensures the predicted values of the dependent variable lie within the empirically plausible range.
Also see Gallani and Krishnan (2017) for the application of FRM in survey research in Accounting.
This method improves upon the two-limit Tobit model which is the frequently used alternative for such data. We carry out the sensitivity analysis for the baseline regressions, by changing the methodology to the two-limit Tobit model. Although the marginal effects of the two-limit Tobit analysis show that the significant, negative effects of commodity prices on the default rate hold without significant differences in magnitude, the two-limit Tobit model does not allow the variation of average marginal effects (AMEs) with respect to the variation of the price index. The results for the two-limit Tobit model are available upon request.
As Papke and Wooldridge (2008) note, the Probit function leads to computationally simple estimators in the presence of unobserved heterogeneity or endogenous explanatory variables.
See Equation (3.1) in Papke and Wooldridge (2008) for the PWNLS estimator.
We consider a geometric distributed lag model \(\left( \tilde{\rho }\in \left[ 0,\,1\right] \right)\) for the level variable:
$$\begin{aligned} \frac{\tilde{\beta }}{\sum _{s=0}^{3}\tilde{\rho }^{s}}\left( \ln P_{t-1}+\tilde{\rho }\ln P_{t-2}+\tilde{\rho }^{2}\ln P_{t-3}+\tilde{\rho }^{3}\ln P_{t-4}\right) , \end{aligned}$$and the maximization of likelihood results in \(\tilde{\rho }=0\). We do not include current commodity price index to avoid the endogeneity problem.
We consider a geometric distributed lag model \(\left( \rho \in \left[ 0,\,1\right] \right)\) for the change variable:
$$\begin{aligned} \frac{\beta }{\sum _{s=0}^{3}\rho ^{s}}\left[ \ln \frac{P_{t}}{P_{t-1}} +\rho \ln \frac{P_{t-1}}{P_{t-2}}+\rho ^{2}\ln \frac{P_{t-2}}{P_{t-3}}+\rho ^{3}\ln \frac{P_{t-3}}{P_{t-4}}\right] \end{aligned}$$and the maximization of likelihood results in \(\rho =1\).
Lopez-Espinosa et al. (2017) show that high expected GDP growth and low domestic credit-to-GDP ratios protect countries against sovereign risk especially in times of global distress.
Reinhart et al. (2016) show that for countries that are not primary commodity producers, the association between default cycle and collapsing commodity prices are not significant. Eberhardt and Presbitero (2021) show that the effect of commodity price volatility on banking crises is especially concentrated in low-income countries with a fixed exchange rate regime and a high share of primary goods in production.
We investigate the impacts from the commodity export and from the indebtedness on the effect of commodity prices in the cross-country analysis in Sect. 6, after discussing the overall effects of the commodity price index and its associated endogeneity tests.
We estimate and choose the relative weights on the level and change variables in the composite-based on the maximum likelihood criteria. For those composite-based specifications, which return the same highest likelihood, we further select the specification that returns the highest AME at the first quartile of the composite price index.
See Papke and Wooldridge (2008), Equation (4.5) and (4.6).
We use the commodity export share of the year 1992 for Russian Federation and Ukraine, as data for these countries starts from 1992. Similar to our price index constructed in Sect. 2, the IVs are deflated by the US CPI and transformed to level and change specifications, respectively.
We also estimate the reduced form in Step 1 for each year (cross-section) with the Bartik instrument and the World Commodity Price Indices instrument, respectively. In those cases as well, no endogeneity issues are observed based on the coefficients of the estimated residuals in Step 2.
The detailed results are available in the online Appendix B, Table B.1 (a), and show that the direction of the effects of the price index and other macroeconomic fundamentals essentially remain unchanged compared to the baseline regressions.
The detailed results for this case are also available in the online Appendix B (Table B.1 (b)) and again show that the direction of the effects of the price index and other macroeconomic fundamentals essentially remain unchanged compared to the baseline regressions.
We don’t include Russia Federation and Ukraine as the data of these two countries covers a much shorter time span.
In the analysis of the effect of commodity prices on banking crises for low-income countries, Eberhardt and Presbitero (2021) show that the impact from the commodity price volatility is especially concentrated in countries with a high share of primary goods in production. Moreover, as shown in Kaminsky and Reinhart (1999), banking crises typically precede currency or balance-of-payments crises.
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We thank Tamon Asonuma, Seungjun Baek, Paul Beaumont, Javier Cano-Urbina, Santanu Chatterjee, Mikhail Dmitriev, Gary Fournier, John Gibson, Chengye Jia, Shawn Kantor, Berna Karali, Carl Kitchens, Jonathan Kreamer, Milton Marquis, Leonardo Martinez, Anastasia Semykina, Cynthia Yang, and all other participants at FSU Macro Workshop and Quant Workshop, 12th Southeastern International/Development Economics Workshop held at the Federal Reserve Bank of Atlanta, IMF Institute for Capacity Development Lunchtime Seminar, 27th International Conference in Computing in Economics and Finance held at Keio University, and SEA 91st Annual Meeting for their valuable comments and suggestions. All errors remaining are ours.
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Atolia, M., Feng, S. World commodity prices and partial default in emerging markets: an empirical analysis. Rev World Econ (2023). https://doi.org/10.1007/s10290-023-00510-8
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DOI: https://doi.org/10.1007/s10290-023-00510-8