 Disaster learning and aggregate investmentYingjie Niu, Jinqiang Yang and Zhentao Zou Journal of Economic Theory, 2024, vol. 220, issue C Abstract: We extend a production-based asset pricing model by introducing learning about disaster risk. The information is not perfect, and Bayesian learning is adopted to update beliefs about the likelihood of rare disasters. We show that disaster learning reconciles key stylized facts about macroeconomic quantities and financial markets. For macroeconomic quantities, during the crisis, the decline in aggregate investments is much worse than that of output, whereas the decline in aggregate consumption is moderate relative to that of output. Additionally, the model endogenously features lower consumption volatility and higher investment volatility than that of output. For financial markets, belief updating over a rare disaster produces a higher equity premium, lower risk-free rate, and more volatile stock returns. Finally, we show that jump intensity uncertainty accounts for a substantial fraction of the total welfare cost of rare disasters. Keywords: Learning; Rare disaster; Jump size; Growth volatility; Equity risk premium (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:jetheo:v:220:y:2024:i:c:s0022053124000784 DOI: 10.1016/j.jet.2024.105872 Access Statistics for this article Journal of Economic Theory is currently edited by A. Lizzeri and K. Shell More articles in Journal of Economic Theory from Elsevier |
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