"Disaster Risk through Investors’ Eyes: a Yield Curve Analysis" [pdf]
This paper develops a model to estimate investors’ perceived probability of disaster from yield curve data. Disasters are extreme events like defaults or interstate wars with significant economic impact. By integrating an asset pricing model with government bond yields from Datastream, I provide daily estimates of the one-year-ahead disaster probability as perceived by investors for approximately 60 countries from 2000 to 2023. The use of yield curve data offers a high-frequency measure of disaster risk that can rapidly incorporate new information. Several facts indicate that the estimated probabilities have predictive value. Probabilities spike before disaster events, such as the debt restructurings of Greece, Sri Lanka, and Ghana, and the onset of the Russia-Ukraine war. They are also strongly associated with higher-risk credit ratings. In a forecasting exercise using machine learning, the estimated disaster probabilities enhance the predictive power of credit ratings. This demonstrates the informational value of bond market data in predicting events.
Working Papers
"Caught in a Trap: Simulating the Economic Consequences of
Internal Armed Conflict" with Hannes Mueller
[pdf]
This study proposes a statistical model to capture the economic impact of the "conflict trap" phenomenon - a period of recurring outbreaks of internal armed conflict. The framework captures conflict dynamics through a discrete-time Markov process. We estimate the transition matrix and link the states to GDP per capita growth distributions through country fixed effects regressions. This allows for simulating the distribution of developmental effects of the conflict trap. We find that the trap has a large detrimental effect on long-term economic development, reaching a relative decline of GDP per capita of over 50% in the most affected countries.
"Coordination Effects among Global Games: An Application on Tax Havens"
[pdf].
Regime change global games are coordination games with incomplete information in which an entity's regime changes if a sufficiently large number of agents take a certain action. This paper extends the game to multiple entities to account for the possible coordination effects among them. To analyze this, I design a model where multiple regime change global games take place simultaneously, and in an ex-ante stage, agents decide which one they play. Then, I compare the effects of altering the public information on the overall coordination. The whole model is conducted using a tax evasion application. My results show that worsening the public information of just one tax haven can increase (ease) or decrease (hinder) evasion (coordination), depending on the relative perception of each one. When the tax haven with the best public perception for evading is threatened, it leads to less evasion. However, if the tax haven with the worst public perception is threatened too harshly, it leads to more evasion due to a Crowding-in effect. Whereas a symmetric worsening always hinders coordination. Therefore, modeling a single entity global game when, in fact, players could choose among several of them, might be missing notorious coordination effects. Indeed, these effects can explain the inefficacy of the international policies to undermine tax evasion. Yet, the oncoming Minimum Global Tax Rate will reduce evasion.
"On the Measurement of Fragility"