investors’ expectations about it. If the fundamentals are good—or everyone expects them to be good—then disagreement about the fundamentals decreases. The lag of the crises in the potentially-affected countries shows a positive and significant effect on uncertainty. Past stock market volatility also has a strong positive and significant effect on uncertainty. Additionally, we use the financial, economic, and political risk indices from ICRG as a summary of risk factors in the economy, influencing the level of uncertainty. The coefficients on these variables are mostly not significant in the regressions.

To summarize the findings of the first step of our analysis: The analysis shows that surprise crises, such as the Mexican, Russian, and Thai crises, significantly increased our measure of uncertainty in other countries. Meanwhile, anticipated crises, such as the Argentinean, Turkish, and Brazilian crises, _decreased_ uncertainty in other countries. These findings are in line with the hypotheses derived from the theoretical model.

# **4.3.2 Effect of increased uncertainty on the probability of a crisis**

In the second step of the analysis, we show that increased uncertainty regarding fundamentals increases the probability of a crisis in a country. We begin by running a pooled probit regression of the incidence of a crisis in a country on the interaction of uncertainty in that country with the incidence of an initial crisis, controlling for a set of other factors, as specified in equation (14). Apart from the controls for country effects and the U.S. long-term interest rate in financial centers, the control variables can be classified into two categories: (1) alternative contagion channels, which could influence the likelihood of a crisis in the potentially-affected countries, and (2) domestic control variables.

Table 2 displays the results of this regression. The first two columns of Table 2 show that the uncertainty variable has a positive and strongly significant effect on the probability of a crisis in a particular country. Column (2) shows that the effect is stronger in emerging economies, once again possibly reflecting the greater degree of information asymmetry in these economies. As a robustness test we also run logit regressions. While column (3) shows that the positive effect of uncertainty on the probability of a crisis is not significant at conventional levels in the set of all countries, column (4) shows that the effect is positive and significant for emerging markets when assuming a logistic distribution. Introducing the dummies into the pooled probit and logit regressions does not seem to create a severe incidental parameter problem, as is apparent from the results using the linear probability model in columns (5) and (6). The magnitude of the effect is smaller, but the effect is still strongly significant and not negligible. These results continue to hold when we only consider the set of surprise crises, which were found to increase the level of uncertainty in other countries (see Table 6 in the Appendix).

With regard to alternative contagion channels, the following variables are controlled for: the common creditor channel of contagion, the direct trade channel, contagion from important stock markets, and contagion through common overexposed fund investors. If not controlling for overexposed common fund investors, we find that common creditors and trade shares have a high explanatory power for the occurrence of a crises in the potentiallyaffected countries (see Tables 2 and 6). However, when we additionally control for overexposed common fund investors, these two variables become insignificant (see Table 7 in the 20