- (1) 250, and (b) above 2 deaths per 100,000 population.

- (2) For rapidly declining security situations according to ACLED, (a) an absolute number of conflict deaths above 250, (b) between 1 and 2 deaths per 100,000 population, and (c) the number of casualties has more than doubled in the past year.

Difference in difference methodology relies on different assumptions where the common trend is the most important one. To validate this assumption of common trends before the flood, indicating that the dependent variable for both groups would have continued moving similarly in the absence of the extreme event, we conduct a test by comparing changes in the dependent variable for the treatment and control groups over multiple periods preceding the floods (i.e. estimate the difference-indifference between t-2 and t-1, the t-3 and t-2, etc.) _._ This analysis helps ascertain whether the economic trajectories of the two groups were indeed parallel before the occurrence of the flood events. The regression is specified as:

- events. The regression is specified as: = T T T 1 + P P 2 + Treatment 3 4

- ii,tt ii tt ii,tt ii,tt

- YY TT ββ PPTT PPT TT ββ ββ + ccPPccT PPT TTPP ββ + εε

(2) statistical tests as well as the common trend visually represented for each of our case study.

# Case study selection

The study’s focus on disaster impacts in conflict vs non conflict affected areas limits the pool of country case studies. There are several aspects that determine the choice of the case study countries. First, the selected countries need to have geographically localized conflicts, allowing for a controlled comparison where conflict is the primary differing factor of disaster impacts. Second, there is a requirement that the selected countries were affected by a rapid onset disaster in recent years, to increase the possibility of available data in assessing the disaster’s impacts. If multiple countries are selected, the rapid-onset disaster events had to happen within the same time frame. This criterion ensures that the case studies provide a focused examination of the impact of disasters on economic activities in conflict setting vs non conflict settings, without the confounding effects of different country conditions or timelines of disaster events. Third, the disaster footprints should cover a substantial geographical extent of the selected countries’ area as opposed to localized disasters. This criterion is to ensure that there are both conflict- and non-conflict-affected areas hit by the disaster. Given the criteria above, we selected the 2019 Tropical Cyclones Idai and Kenneth in Mozambique and the July 2022 floods in Nigeria as case studies. Furthermore, the two countries have comparable contexts in terms of conflict characteristics which are crucial for isolating the variable of conflict in comparative analysis.

# Mozambique case study: 2019 Tropical Cyclones Idai and Kenneth

Mozambique was hit by two Tropical Cyclones (TC), Idai (March 4-15) and Kenneth (April 25-28), both of which have been qualified as among the strongest TCs on record in the Southern Hemisphere (Charrua et al., 2021). The northeastern region of the country is characterized by a widespread long9