yield a consistent albeit inecient estimator under the null of cointegration). Results will prove to be similar in both cases.

Standard lag tests suggest estimating the model including two annual lags (Schwartz information criterion). Three annual lags are also considered for robustness.

The parameters of the two versions of the model, estimated in reduced form by OLS (eq. [1]) or SURE (eq. [2]) are used to recover the impulse-response functions (IRF) of per capita GDP to each of the structural shocks using the variance-covariance matrices of reduced form errors derived from these coecients. The condence bands for the IRF come from parametric bootstrapping on the model assuming normally distributed reduced form errors.<sup>5</sup>

# 4 Results

This section presents the results from the estimation of the panel ARDL and panel VAR models described above in the sample of countries that have experienced at least one large climatic disaster since the 1950s. It rst describes the results on the sample as a whole and then presents results for sub-groups of the sample, split according to characteristics that have been mentioned to aect a country's vulnerability to disasters.

## 4.1 The output impact of natural disasters

The dynamic responses of output to the various types of natural disasters obtained from the estimation of the parameters of equation (1) are depicted in Figure 4. The dierent panels of this gure show the cumulative impulse-response functions (IRF) of (the growth of) real per capita GDP ( _GDP_ ) to each type of natural disaster, under the benchmark identication assumptions. Since the model was estimated in growth rates, the cumulative IRF show the cumulative output eect of each of these shocks. The continuous line depicts the point estimate of the IRF, and the broken lines show the 90% condence bands obtained from the empirical distribution.

Climatic disasters have, on average, a negative, statistically signicant impact on per capita GDP (Panel A), which has a cumulative decline of 0.6 percent after a large climate related catastrophe. In other words, in the long run, per capita GDP is 0.6 percent lower as a result of a single climatic event. Most of the output cost (about 0.5 percent loss) occurs during the year of the disaster. In contrast, geological disasters do not have a statistically signicant output impact, and a slightly positive longrun associated point estimate (Panel B). Other types of disasters (which include famines, epidemics, etc.) also negatively aect output, with an estimated cumulative output loss of about 2 percent (Panel C) that is larger that that of climatic disasters, but less statistically signicant.

> 5The procedure corresponds to repeating 100 times the following set of steps: (i) the estimated variance-covariance matrix of the reduced form errors is used to simulate a random realization of the perturbations; (ii) the initial values of the dierent variables, the baseline coecients, and the simulated perturbations are used to simulate a new set of observations for the variables in the VAR; (iii) a new set of coecients is obtained from these ctitious observations. Each set of coecients obtained from the bootstrapping procedure yields a dierent IRF; these IRFs are used to build the 90% condence interval by computing the Euclidean distance between each simulated IRF and the baseline one and taking those IRFs whose distance falls between the 5th and 95th .percentile.

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