icy and Institutional Assessment (CPIA) from the WDI), and sovereign wealth funds (country economists).

- **Macroeconomic indicators** : Core measures to calculate ratios, real variables and general indicators of economic health include real and nominal GDP, exports, public debt, the consumption price deflator, real and nominal exchange rates, average interest rates, credit spreads on public debt, public expenditures and revenues, the current and capital accounts of the balance of payments, credit ratings and default episodes (MPO, WDI, WEO, Bank of Canada, Bloomberg), and non-performing loans (WDI).

The methodology aggregates the above mentioned variables into a single index. The weights are estimated via a standard dimension reduction technique (e.g. dynamic factor models or principle components) using data starting from 2002. The advantage of this technique is that weights are neutral and completely dependent on the data. This methodology controls for country characteristics, where individual series might have a different weight across countries in each index (see Appendix A for more details on the methodology).

The proposed index measures whether country debt vulnerabilities are increasing or abating: (i) an increase in the vulnerability index highlights risk build-up, (ii) an increase in the vulnerability index relative to its trend highlights risk build-up with respect to its history, or (iii) an increase in the country index relative to regional trends to identify large outlier countries within a region. An increase in the resilience index implies that countries are building up buffers against possible unexpected shocks.

Principal components analysis (PCA) is used for extracting the vulnerability index from the annual data module. PCA is appealing because of its computational advantages and asymptotic properties in large data sets (see Bai (2003)).

After estimation, a fundamentals vulnerability index is generated. Figure 5 illustrates build-up of public and private debt vulnerabilities within each country using the proposed index. It is important to note that an increase in each of the variables used in the index point to an increase in vulnerability, such that the index has the same interpretation and such that the weights are positive (i.e., an increase in the index implies an increase in one of the variables - e.g., larger foreign denominated debt issuance will contribute to an increase in the index).

The black dots in Figure 5 represent the debt vulnerability indices by country while the red lines are the country trends of these indices (i.e. by construction the average is roughly zero). The figure summarizes vulnerability since 2002, while the making of each country’s index takes the full sample size (which differs by country) into account.<sup>3</sup> A positive value indicates that a country is now more vulnerable than, on average, in the past. As an example, Argentina’s index has been rising steadily since 2012 and is above its trend. Using this measure, ex post, one would have inferred rising vulnerabilities faced by Argentina and using the decomposition chart in the Appendix, that most of the risk was emanating from upcoming amortization. Other countries in the sample (e.g., Brazil and Belarus) also have rising vulnerabilities, however, have not defaulted (in Brazil’s case, probably because foreign debt is a very small share of its large public sector debt).

> 3See Appendix E for the same chart but for the resilience indicator.

9