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Hvis der skal skabes varig forandring i forbrugernes madvaner, er der behov for en koordineret indsats mellem offentlige og private samt investering i samfundsvidenskabelig forskning.

Late 2020, The Danish Environmental Protection Agency issued an order for determining the level of climate adaptation (Ministry of Environment, 2020). The new order requires municipality councils and utility companies to perform a socio-economic analysis when determining the level of climate adaptation. After its release, the order has been criticised for not including different non-marketed benefits into the socio- economic analysis. Our thesis starts by examining the element that is currently the largest share of the benefits in the socio-economic analysis, namely damage costs that can be avoided by climate adaptation. We find that the currently used values rely on weak assumptions and seems to be overestimated. To improve these values, we propose three estimations, all by ordinary least square method. First, we estimate an ‘easy to implement’ national value. Second, we estimate two models with house/apartment characteristics, where one of the two models include fixed effect on municipalities. Second, we investigate whether the order should account for cloudbursts damages effect on house prices. Our analysis is based on a Difference-in-Difference design, in which we use data from a cloudburst that occurred in the Copenhagen metropolitan area on the 2nd of July 2011. We estimate six different Difference-in-Difference designs accounting for damage or risk of damages. Two of the six models are dynamic. In our analysis we find no significant effect on house prices, neither for cloudburst damage or risk of cloudburst damages. Third, we analyse whether the order should include the non-marketed value of nature- based solutions. Through a literature review, we argue the need for new valuation studies, especially for urban greening projects. We recommend the further valuation studies ideally should result in a catalogue or benefit transfer function. Finally, we apply our findings on an already calculated case, to exemplify the implications of our findings. The case

Late 2020, The Danish Environmental Protection Agency issued an order for determining the level of climate adaptation (Ministry of Environment, 2020). The new order requires municipality councils and utility companies to perform a socio-economic analysis when determining the level of climate adaptation. After its release, the order has been criticised for not including different non-marketed benefits into the socio- economic analysis. Our thesis starts by examining the element that is currently the largest share of the benefits in the socio-economic analysis, namely damage costs that can be avoided by climate adaptation. We find that the currently used values rely on weak assumptions and seems to be overestimated. To improve these values, we propose three estimations, all by ordinary least square method. First, we estimate an ‘easy to implement’ national value. Second, we estimate two models with house/apartment characteristics, where one of the two models include fixed effect on municipalities. Second, we investigate whether the order should account for cloudbursts damages effect on house prices. Our analysis is based on a Difference-in-Difference design, in which we use data from a cloudburst that occurred in the Copenhagen metropolitan area on the 2nd of July 2011. We estimate six different Difference-in-Difference designs accounting for damage or risk of damages. Two of the six models are dynamic. In our analysis we find no significant effect on house prices, neither for cloudburst damage or risk of cloudburst damages. Third, we analyse whether the order should include the non-marketed value of nature- based solutions. Through a literature review, we argue the need for new valuation studies, especially for urban greening projects. We recommend the further valuation studies ideally should result in a catalogue or benefit transfer function. Finally, we apply our findings on an already calculated case, to exemplify the implications of our findings. The case