Climate Change and Long-Horizon Portfolio Choice: Combining Theory and Empirics

We propose a novel approach for measuring the impact of climate change on long-horizon equity risk and optimal portfolio choice. Our method combines historical data about the impact of climate change on return dynamics with prior beliefs elicited from the temperature long-run risk (LRR-T) model of Bansal, Kiku, and Ochoa (2019). Our Bayesian framework incorporates this prior information to obtain more precise estimates of long-term climate risks than existing methods that solely rely on historical data. Compared to the benchmark investor without climate change, we document that the LRR-T Bayesian investor predicts higher equity premia for all investment horizons, with per period variance increasing considerably over the horizon. This results in relatively (high) low allocations to equities in the (short) long run. Investors that optimize between portfolios that are vulnerable and non-vulnerable to climate change only diversify in the long run.