key to debt sustainability (see also Reinhard and Rogoff, 2010).

The paper is structured as follows. In section 2, we review key findings in the literature of potential determinants of sovereign defaults. In section 3, we present our dataset for 46 EMCs, as well as stylized empirical facts related to debt default. In section 4, we isolate robust determinants of default episodes among variables representing macroeconomic fundamentals, liquidity and solvency risks, as well as quality of policies and institutions. The use of BMA allows us to identify those variables that are most robust to changes in the set of conditioning variables. Finally, in section 5 we draw conclusions and present policy recommendations.

# **2. On the empirical determinants of sovereign default**

Empirical models of sovereign default vary sometimes strongly in the choice of control variables. Most studies start by identifying sovereign defaults based on some definition (which is not necessarily consistent across studies) and build binary dependent variable models, generally logit or probit models, to assess the statistical significance of different potential determinants of debt crises. Table 1 presents a selection of recent empirical contributions of this type, together with the identity of the variables used as explanatory covariates in their respective models. Although there are remarkable differences in the choice of explanatory variables, in general empirical sovereign default models tend to include determinants which can be easily clustered into differentiated groups.

Firstly, country‐specific _macroeconomic fundamentals_ mirroring the effectiveness of economic policy and developments in the real economy tend to be systematically added as potential determinants of the probability of default. These include GDP growth, current account developments, fiscal and monetary policy variables and measures of real exchange rate misalignment. In addition, measures of the quality of countries’ policies and institutions are also widely used to capture the effects of soft‐factors, such as institutions, corruption and governance that are not directly considered by macroeconomic variables. Measures of _external solvency and liquidity_ proxy the repayment capability of the country and are also systematically included in binary dependent variable models aimed at predicting sovereign default. Among these covariates, the extent and composition of external debt plays a privileged role as an explanatory variable and is usually the object of analysis of most empirical contributions to the determinants of default _._ _External shocks_ are also represented in the set of determinants by such variables as the US real interest rate. The effect of external developments on country‐specific default probabilities can be thought of as mediated by the degree of external exposure of a given economy, which justifies the inclusion of trade and financial openness measures in debt default models.

In our robustness analysis we use representative variables of each one of these groups in order to evaluate their relative importance in the framework of model uncertainty. In addition, we also add a group of new variables which we label “ _debt management variables”_ to account for the importance of the structure and characteristics of the existing external 3