Extreme weather events in Finland – a dynamic CGE-analysis of economic effects

Due to the climate change, the frequency and magnitude of extreme weather events, such as flooding and droughts, are predicted to increase in many parts of the world. Extreme weather events may cause significant material and human losses. In our study, we wanted to investigate how these events would affect the Finnish economy as a whole and what would be the economically optimal strategy for both the prevention and aftermath. Until recently damage and risk assessments tended to focus on direct costs only. Our study, however, takes into account both the direct and indirect effects. We based our analysis on two cases of regionally diversified flooding events in Finland. In the first one we studied a heavy rainfall event in the capital city Helsinki, and in the second one a river flooding case in a smaller industrial town Pori. These locations differ by their economic structure in themselves and in relation to the rest of the economy. Helsinki has bigger economy in overall with higher share of service industries than Pori. Helsinki also exports more of its commodities to the other regions in the country. Based on an earlier assessment, we were able to formulate direct and indirect economic shocks caused by the capital loss for two separate magnitudes of flooding events. We used a dynamic regional CGE-model for Finland, VERM to simulate the economic effects. VERM has bottom-up structure with 20 regions (NUTS3-level) and 46 industries. With the model, we compared three different strategies for compensating the losses. In the first one, the industries themselves were responsible for their repair costs. Two alternative scenarios portrayed the cases where public authorities and private insurance sector financed the rebuilding, respectively. We found that the most efficient way to recover from a flood is to let the industries themselves pay the bill– the alternative scenarios both lead to less efficient recovering paths. Rebuilding happens fastest in the insurance sector scenario, but this fast rebuilding option seems to be the most inefficient one as well since it drives investment prices to a very high level. In all cases, the flooding will cause permanent negative deviation from the baseline GDP level and an increase in employment. GDP decreases mostly due to capital loss and employment increases mostly because of increased demand for construction industry. Even after 15 years, a structural shift to more labor intensive economy is visible in our results. We also found out that the long term overall effects are likely to be at least two times higher than the initial effects caused by the flood and thus the initial damage should be considered as an underestimation of the real costs. An interesting and also a bit controversial result was a regional disparity that we found – although the direct losses of Helsinki floods are smaller than those of Pori, the effects for the entire economy were much larger. This is caused by the capital region’s stronger connections with the other parts of the country. This result indicates that if we are to consider the measures for preparing for the floods we should not only look at the amount of direct and indirect losses but also the significance of the region for the whole economy