Welfare Consequences of Persistent Climate Prediction Errors on Insurance Markets against Natural Hazards

Abstract

This paper studies the welfare consequences of the friction between two groups, those with and those without rational expectations, in an incomplete insurance market. We validate this friction empirically and test the existence of additional heterogeneity in the probability of belonging to the group which makes persistent mistakes on the anticipation of climate events using econometric models. The econometric models further suggest that the probability of belonging to this group varies significantly by sociodemographic attributes of respondents and by the geophysical attributes of their places of residence. Based on this evidence, we develop a two-period model of private insurance under uncertainty with endogenous prices. By including a central planner providing a technology for access to accurate information, our example illustrates that public intervention (via taxation) would only be feasible if public expenditure in the provision of this technology did not exceed 9.188% of the aggregate income earned by agents with inaccurate expectations.

Profiling sociodemographic attributes and extreme precipitation events as mediators of climate-induced disasters in municipalities in the state of Minas Gerais, Brazil

“…When comparing data regarding monthly precipitation and surface air temperature averages for 1961-1990and 2071-2100, Torres et al (2012's results differ from ours because their focus on future climate change sensitivity hides the ability to fully discern the heterogeneity of current climate vulnerability. Furthermore, their results were not able to spatially map climate-induced disasters-events that are more readily translated into welfare losses (Guedes et al, 2019;Araújo et al, 2020). Our results show that cities with better developed infrastructure and more advantaged sociodemographic profiles located in semi-arid regions of Minas Gerais are more resilient to droughts.…”

“…Theoretical findings from Raad et al (2019) show that the demand for insurance against climate-induced disasters declines due to climate uncertainty. Building on a previous study, Guedes et al (2019) used time series data obtained from meteorological stations, coupled with Digital Elevation Models (DEM), data on flooding events, and primary survey data on local perceptions of meteorological changes to understand the extent of welfare losses due to degree of perception errors concerning disaster occurrence. The dissonance between the perception of and the actual occurrence of disasters led to a major decline in insurance acquisition, causing an aggregate welfare loss.…”

“…Greater efforts to enhance and expand scientific communication regarding climate change and its consequences may help reduce the uncertainty surrounding climate-induced events. This could lead to the more efficient adoption of preventive measures, preventing unnecessary losses in agents' wellbeing due to incomplete information (Guedes et al, 2019).…”

Health-related vulnerability to climate extremes in homoclimatic zones of Amazonia and Northeast region of Brazil

“…In places where infrastructure or adaptive measures are inadequate, these impacts can be more severe, ultimately leading to loss of human life [ 2 , 4 , 22 , 59 ]. Thus, identifying socioenvironmental deprivation and exposure to these events is key for decision makers to properly address a population’s health vulnerabilities and establish strategies to mitigate adverse effects on climate-sensitive diseases [ 88 ].…”

Visualizando a relação entre testes em modelos de TRI multi-unidimensionais

“…O projeto foi aprovado pelo Comitê de Ética em Pesquisa da Universidade Federal de Minas Gerais (Protocolo CAAE 12650413.0.0000.5149). Os dados da pesquisa já foram analisados em outros contextos em (Araújo et al, 2020;Guedes et al, 2019), aonde é possível encontrar mais detalhes sobre os dados.…”