Prospects for rare economic disasters have major effects on markets for stocks, bonds, and other assets. This project incorporates these disasters into a model. The analysis assumes a low probability of a disaster in which output falls by a substantial proportion. Contingent on economic disaster, there is another probability of partial default on bills, usually through high wartime inflation. Disaster risks can explain a number of financial puzzles, including the low rate of return on safe assets, the high equity premium, and the high volatility of stock returns. The model can also explain why expected real interest rates were low during U.S. wars back to the Civil War and continuing to the post-September 11th period. These results come from a tractable framework that allows for analytical solutions. The investigator uses the 20th century global history to gauge model parameters related to economic disasters. This history is dominated by WWI, the Great Depression, WWII, and post-WWII depressions outside the OECD. For 35 countries and 100 years of data, there were 60 short-term contractions of per capita GDP in the range between 15% and 64%. Based on this pattern, the investigator assumes a disaster probability of 1.7% per year and a frequency distribution of disaster sizes that matches the observed distribution. The conditional default probability is set at 40% to fit the observed frequency of low bill returns during wartime economic disasters. The conditional size of default is set to equal the size of contraction to replicate the similarity in average returns on stocks and bills in these circumstances. The investigator calibrates the model using these disaster parameters and other parameters related to GDP growth and household preferences. The simulated model's predictions accord in many respects with the history of returns on stocks and bills.
The most important next step is to extend the model to incorporate random, persisting variations in the disaster probability, pt. This extension should help to explain the volatility of stock prices and the time series realizations of real interest rates and price-earnings ratios. A major empirical project is to measure pt and to relate these values to asset returns and consumption. Ideas for measuring perceived disaster probabilities include options prices on stock markets, insurance premia, contract prices in betting markets, and the "minutes to midnight" in the atomic clock. Additional information will come from the theoretical relation of pt to various asset prices and rates of return, including gold prices, real interest rates, price earnings ratios, options prices, and real estate prices. Another important project is the assembly of annual data on consumer expenditure and asset returns over long periods for the G7 countries and for a few other countries with available data. This information is used to assess disaster probabilities and sizes and to gauge the extent to which disasters have persisting influences on levels of per capita GDP. Further analysis is devoted to explaining rates of investment and economic growth and to distinguishing global from local disturbances. The analysis is also applied to open economies to understand puzzles related to interest-rate parity conditions.
Broader Impacts: The central idea is that the potential for rare disasters explains a lot of financial puzzles within a tractable model. The disasters include not only depressions and wars but larger versions of recently discussed natural disasters hurricane Katrina, the Indian Ocean tsunami, and avian flu. The financial puzzles include a high equity premium, low rate of return on comparatively safe assets, volatility of stock prices, and low real interest rates during most U.S. wars. The key point is that a heightened disaster risk raises the demand for safe assets, such as government bills, and thereby lowers real interest rates on these assets. If the project's perspective is correct, the rare-disasters framework could become a basic part of standard analyses used by researchers in macroeconomics and finance.
