the generality and external validity of the conclusions. A dierent strand of this literature has started to use broad recently-available data sources to provide systematic evidence on the macroeconomic impact of disasters. Skidmore and Toya (2002) study the long-run growth consequences of natural disasters using data on the incidence of several types of disasters on a large sample of countries. They use cross-country regressions to determine the relation between the incidence of disasters (measured as the total number of disasters per land area) and growth, and nd a positive eect of climatic disasters and a negative eect (although not always signicant) of geological disasters. Although the paper controls for several country characteristics, the possibility of omitted variable bias and endogeneity cannot be ruled out in this setting.<sup>2</sup> To overcome some of the problems associated with the cross-country approach, other papers have exploited the within country, time-series variation in the occurrence of disasters. Ramcharan (2007), and Noy (2009) use standard dynamic panel specications to estimate the impact of disasters on various aspects of macroeconomic performance. Ramcharan (2007) estimates the dierential impact of earthquakes and windstorms in 120 countries with xed and exible exchange rate regimes during the period 1961-2000 to test the hypothesis that a exible exchange rate helps smoothing real shocks. Noy (2009) uses similar data to estimate the short run impact of disasters on growth controlling for the magnitude of a disaster and to relate the impact to structural characteristics such as the quality of institutions, nancial development, and human capital. The close relation of these papers with the dynamic panel literature leads them, however, to not fully exploit the time variation of the data and to rely on restricted functional forms and identication assumptions. In particular, they impose the lag structure instead of deriving it from standard lag tests, assume rst dierence stationarity instead of testing for the stationarity of the variables, and rely on some controversial identication assumptions: exogeneity of exchange rate regimes in the case of Ramcharan (2007) and predeterminedness of variables (which is sensitive to the lag specication) in the case of Noy (2009). A recent paper by Raddatz (2007) addresses some of these problems using standard timeseries techniques in a PVAR model, and relying on identication assumptions based mainly on the exogeneity of external shocks. However, this paper studies the impact of a broad set of external shocks and, therefore, treats natural disasters in a highly parsimonious manner that disregards part of the information contained in specic types of shocks and also group disaster prone countries with those that have never experience these types of episodes.

This paper contributes to this literature by providing systematic evidence on the output cost of natural disasters coming from a large and comprehensive set of dierent types of catastrophes on a large sample of countries and over an extensive period of time, applying standard time-series techniques that exploit mainly the within-country time series variation of the data and provide a natural manner of assessing the short and long run impact of disasters, and only relying on relatively uncontroversial assumptions about the exogeneity of disasters from within country output uctuations.

> 2Although the occurrence of disasters is arguably exogenous, the criteria used to record events in the existing databases make disasters occurring in poor countries more likely to be recorded. Pure cross-country variation does not permit to control for this possibility.

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