Template-Type: ReDIF-Paper 1.0 Author-Name: Jacob Pastor-Paz Author-X-Name-First: Jacob Author-X-Name-Last: Pastor-Paz Author-Email: jacob.pastor.paz@gmail.com Author-Workplace-Name: Victoria University of Wellington Author-Name: Ilan Noy Author-X-Name-First: Ilan Author-X-Name-Last: Noy Author-Email: ilan.noy@vuw.ac.nz Author-Workplace-Name: Victoria University of Wellington Author-Name: Isabelle Sin Author-X-Name-First: Isabelle Author-X-Name-Last: Sin Author-Email: isabelle.sin@motu.org.nz Author-Workplace-Name: Motu Economic and Public Policy Research Author-Name: Abha Sood Author-X-Name-First: Abha Author-X-Name-Last: Sood Author-Workplace-Name: National Institute of Water and Atmospheric Research (NIWA) Author-Name: David Fleming-Munoz Author-X-Name-First: David Author-X-Name-Last: Fleming-Munoz Author-Workplace-Name: Commonwealth Scientific and Industrial Research Organization (CSIRO) Author-Name: Sally Owen Author-X-Name-First: Sally Author-X-Name-Last: Owen Author-Workplace-Name: Victoria University of Wellington Title: Projecting the effect of climate change-induced increases in extreme rainfall on residential property damages: A case study from New Zealand Abstract: New Zealand’s public insurer, the Earthquake Commission (EQC), provides residential insurance for some weather-related damage. Climate change and the expected increase in intensity and frequency of extreme weather-related events are likely to translate into higher damages and thus an additional financial liability for the EQC. We project future insured damages from extreme precipitation events associated with future projected climatic change. We first estimate the empirical relationship between extreme precipitation events and the EQC’s weather-related insurance claims based on a complete dataset of all claims from 2000 to 2017. We then use this estimated relationship, together with climate projections based on future greenhouse gases concentration scenarios from six different dynamically downscaled Regional Climate Models, to predict the impact of future extreme precipitation events on EQC liabilities for different time horizons up to the year 2100. Our results show predicted adverse impacts that vary -increase or decrease over time and space. The percent change between projected and past damages—the climate change signal—ranges between an increase of 7% and 8% higher in the period 2020 to 2040, and between 9% and 25% higher in the period 2080 to 2100. We also provide detail caveats as to why these quantities might be mis-estimated. The projected increase in the public insurer’s liabilities could also be used to inform private insurers, regulators, and policymakers who are assessing the future performance of both the public and private insurers that cover weather-related risks in the face of climatic change. We combine firm-level innovation data with area-level Census data to examine the relationship between local workforce characteristics, especially the presence of immigrants and local skills, and the likelihood of innovation by firms. We examine a range of innovation outcomes, and test the relationship for selected subgroups of firms. We find a positive relationship between local workforce characteristics and average innovation outcomes in labour market areas, but this is accounted for by variation in firm characteristics such as firm size, industry, and research and development expenditure. Controlling for these influences, we find no systematic evidence of an independent link between local workforce characteristics and innovation. Length: 25 pages Creation-Date: 2020-02 File-URL: https://motu-www.motu.org.nz/wpapers/20_02.pdf Number: 20_02 Classification-JEL: Q54 Keywords: Insurance, precipitation, climate change, extreme weather-events, loss projection Handle: RePEc:mtu:wpaper:20_02