A Dynamic Framework for Endogenous Climate Risk and Asset Prices

Thesis Abstract

This study develops a dynamic framework to quantify endogenous climate risk and its impact on asset prices, addressing the gap in traditional asset pricing models that treat climate shocks as exogenous disturbances. The research responds to the rising evidence that climate risk is embedded within macro-financial markets and can influence risk premia, beta dynamics, and intertemporal consumption–investment decisions. The aim is to construct a parsimonious yet flexible model that jointly characterizes climate-driven risk channels, including physical risk, transition risk, and policy uncertainty, and to evaluate their effects on asset pricing in equity and fixed-income markets. Specific objectives are (i) to formulate a dynamic stochastic general equilibrium (DSGE) framework augmented with climate state variables that are endogenously determined by emissions trajectories, technological transitions, and policy regimes; (ii) to derive asset pricing implications for equity returns, option premia, and sovereign yields under climate-induced risk scenarios; (iii) to calibrate the model using multi-country panel data covering 25 developed and emerging markets over 1995–2024 and a climate risk index constructed from IPCC scenarios, policy announcements, and carbon intensity metrics; and (iv) to perform counterfactual analyses to isolate the contribution of endogenous climate risk to observed asset price dynamics. The methodology employs a combination of structural estimation and simulation. The population comprises macro-financial variables and climate indicators at the annual frequency; a balanced panel of 25 countries with data on stock index returns, government bond yields, GDP, consumption, investment, and emissions forms the sample. Data collection combines (a) financial time series from Bloomberg and Thomson Reuters Eikon, (b) climate data from the Network for Greening the Financial System (NGFS) scenarios and the Intergovernmental Panel on Climate Change (IPCC) reports, and (c) policy variables from central bank and government sources. The instrument set includes global risk factors, term structure signals, and climate policy announcements to identify exogenous variation in climate risk channels. The model specification extends a two-country DSGE framework with endogenous climate dynamics by embedding climate state variables that respond to accumulation of emissions, technological progress, carbon pricing, and policy stringency. Asset prices are derived via a no-arbitrage condition in a representative agent setting, with preferences incorporating Epstein–Zin utility to capture risk and intertemporal substitution. The estimation strategy combines maximum likelihood with Bayesian nested sampling and particle filtering to fit the dynamic system, while impulse response analysis and variance decomposition assess the relative importance of climate channels. The analysis of equity markets uses panel regression cases with asset pricing tests focusing on the equity risk premium, conditional beta, and downside risk measures, and sovereign markets are examined through term premium and yield curve dynamics under climate stress scenarios. Key expected findings include (i) endogenous climate risk significantly amplifies time-varying risk premia during high policy uncertainty periods, (ii) transition risk, captured through policy stringency and technology diffusion parameters, systematically lowers the price of carbon-intensive assets while raising the risk-adjusted required return on greener assets, (iii) climate state variables contribute to a downward-sloping term premium in long-duration bonds during transition phases, and (iv) model-implied asset prices exhibit improved fit and forecast accuracy relative to standard consumption-based or CAPM-like models, particularly in episodes of climate policy shocks. Robustness checks are performed using subsamples, alternative climate indices, and out-of-sample forecasting. The study contributes to knowledge by providing a coherent dynamic framework that embeds endogenous climate risk into asset pricing, offering a measurable link between climate dynamics and financial decisions, and delivering policy-relevant insights on how climate policy and technological transitions shape asset valuations. The main conclusion is that endogenous climate risk constitutes a systemic channel through which macro-financial linkages operate, warranting explicit monitoring in risk management and asset allocation. Recommendations include integrating climate state variables into central bank stress testing, improving cross-market climate risk disclosure, and prioritizing investments in climate-resilient and low-carbon assets to mitigate Climate-Related Financial Risk.