Impact of Climate Risk on Property Insurance Pricing: An Empirical Study

Thesis Abstract

Urban property insurance pricing increasingly reflects exposure to climate-related risks, yet empirical evidence detailing how climate risk metrics translate into premium adjustments remains fragmented across markets. This study addresses the gap by examining how climate risk factors influence property insurance pricing in a mid-sized coastal economy, where exposure to hurricane, flood, and extreme heat events has risen over the past decade. The aim is to quantify the extent to which climate risk variables affect pricing decisions of property insurers and to identify mediating factors such as underwriting practices and regulatory environment. Specific objectives are (1) to estimate the association between climate risk indicators (historical catastrophe loss experience, flood / windstorm hazard maps, and projected near-term sea-level rise) and quoted premiums; (2) to assess whether risk-based pricing mechanisms differ by property type (residential vs. commercial) and by geographic sub-market; (3) to evaluate the moderating roles of insurer capital adequacy, reinsurance reliance, and regulatory stringency; and (4) to compare observed pricing patterns with theoretical predictions from expected utility and information asymmetry frameworks. The study adopts a quantitative, cross-sectional design grounded in the Risk-Based Pricing theory and the Classical Hedging framework, enabling a test of whether climate risk is priced into premiums beyond traditional exposure metrics. The population includes licensed property insurers operating in the coastal region, supplemented by a stratified sample of 60 insurers and 600 commercial and 1,000 residential property risk quotes sourced from insurer rate filings, brokers, and insureds for the most recent fiscal year. Data collection combines primary instruments (structured surveys of pricing actuaries and underwriting managers, and expert interviews with 12 senior underwriters) with secondary sources (official rate filings, catastrophe model outputs from reputable vendors, and regional climate projections). Validity is ensured through triangulation of premium data with independent catastrophe model outputs and regulator-approved rating factors, while reliability is enhanced via pilot testing of the survey and inter-rater checks for qualitative inputs. Statistical analysis employs multilevel mixed-effects regression to account for clustering by insurer and geographic sub-market, with premium as the dependent variable and climate risk measures (loss experience, hazard intensity indexes, and probabilistic catastrophe indicators) as key predictors. Control variables include property value, coverage limits, deductible levels, construction type, occupancy, policy duration, and inflation-adjusted replacement cost. The model specification tests non-linearities and interaction effects between climate risk and market factors. In addition, a regression discontinuity design is considered to exploit regulatory thresholds that alter pricing discretion. Robustness checks include alternative specifications (log-linear and gamma models for skewed premium distributions), bootstrapped standard errors, and out-of-sample validation using 20% of the data. The analysis is conducted using R and STATA, with diagnostic procedures for multicollinearity and heteroskedasticity. Expected findings indicate a positive and statistically significant relationship between climate risk indicators and property insurance premiums, with stronger effects for commercial properties and in sub-markets with higher hazard exposure. The magnitude of pricing sensitivity is anticipated to be moderated by insurer capital adequacy and regulatory rigor, suggesting differential risk transfer and pricing behavior across the market structure. The study also expects evidence of information asymmetry effects, where limited climate risk disclosure by insureds amplifies premium differentials. The contribution to knowledge includes an empirically grounded assessment of climate risk pricing in property insurance, integrating catastrophe risk analytics with insurer pricing mechanics, and clarifying the role of regulatory and market governance in shaping pricing responses. The findings will inform policymakers on the effectiveness of risk-based capital requirements and disclosure standards, and guide insurers in refining pricing models to reflect climate risk without unintended access-to-insurance constraints. The main conclusion is that climate risk is a material pricing determinant in coastal property insurance, with pricing sensitivity contingent on market and regulatory context; recommendations emphasize standardized climate risk disclosure, enhanced catastrophe modeling integration in pricing systems, and targeted regulatory adjustments to ensure resilience while preserving market participation.