Velasco 2000). Financial and corporate sectors may face liquidity shocks when financing long-term projects with short-term borrowing, as well as currency mismatches due to large foreign-denominated debt. This sets up the possibility of a twin crises—currency and banking—if balance sheets deteriorate rapidly with fluctuations in asset prices, including exchange rates.

Vulnerabilities stemming from large borrowing by banks, in part induced by explicit or implicit government guarantees to bail out failing banks, can trigger crises and be selffulfilling due to fiscal concerns and volatile exchange rate movements (Burnside, Eichenbaum, and Rebelo 2004). Large sovereign exposures can limit banks’ ability to extend loans to the private sector, hence triggering a credit crunch (Gennaioli, Martin, and Rossi 2014). Uncertainty following a debt default may also lead to a deposit run or a collapse of interbank markets (Borenzstein and Panizza 2008). An initial bank run can turn into self-fulfilling cycles of deposit withdrawals, liquidity shortages, and credit crunches (Diamond and Dybvig 1983).

Conversely, bank rescue operations, such as public recapitalization or the materialization of public guarantees and contingent liabilities, may impair the sustainability of public finances thus aggravating the feedback loop from the banking sector to the sovereign (Acharya, Drechsler, and Schnabl 2014). Banking crises may also ignite a currency crash, especially if the central bank monetizes to finance bailouts, thus increasing the risk of the government failing to repay its foreign currency debt (Reinhart and Rogoff 2011).

# 3.2 Methodology

Econometric framework . Studies on the determinants of crises are closely related to early warning system models. Prior early warning models were aimed at predicting currency crises following frequent crashes and devaluations in the 1980s and 1990s and they largely focused on macroeconomic and financial imbalances (e.g. Eichengreen, Rose, and Wyplosz 1995; Frankel and Rose 1996; Kaminsky and Reinhart 1999). Balance sheet variables became more prominent in later early warning models, especially in predicting banking crises (e.g. Demirgüç-Kunt and Detragiache 1998; Borio and Lowe 2002; Rose and Spiegel 2012). Studies on predicting sovereign debt crises emphasize the importance of solvency and liquidity measures, as well as factors that explain currency crises (e.g. Manasse, Roubini, and Schimmelpfenning 2003; Dawood, Horsewood, and Strobel 2017).

The most common estimation methods used in the empirical literature on predicting crises are logit and probit models. The baseline specification used in this study is a panel logit model with random effects, but for robustness purposes, a random effects probit model and a fixed effects logit model are also used. The Hausman test suggests that the random effects model is appropriate for debt and banking crises but not for currency crises. However, even for currency crises, the coefficient estimates and their statistical significance remain similar in fixed effects and random effects models.

To exploit the time and cross-sectional dimensions, a panel dataset of 139 EMDEs with annual data over the period 1970–2018 is constructed. The basic structure of the model takes the form: 9