 |
We propose a simulation-based strategy to estimate and test an asset pricing model that accounts for rare but severe consumption contractions that can extend over multiple periods. Our approach expands the scope of prevalent calibration studies and tackles the inherent sample selection problem faced when empirically assessing the effect of rare disaster risk on asset prices. The application of this new methodology using a combination of U.S. and cross-country panel data yields estimates of the investor preference parameters that are plausible, reasonably precise, and robust with respect to alternative model specifications. The market equity premium and Sharpe ratio implied by these parameter estimates are consistent with empirical data, and the timing premium computed as proposed by Epstein et al. (2014) has an economically meaningful magnitude. These results suggest that the rare disaster hypothesis can help restore the nexus between the real economy and financial markets when allowing for multi-period disasters.
