Time-varying disaster risk, asset prices and international business cycles

This project analyses the relationship between financial asset prices and economic fluctuations. We use an economic model in which asset prices are driven mainly by the investor’s fear of large, but unusual, economic downturns, similar to that observed in 2008-2010. In the model, the likelihood of these events is captured by a time-varying probability model of a fall in income and dividend payout. Our model extends previous frameworks to a general setting where investors’ preferences separately account for their risk aversion and their willingness to substitute consumption in response to a future fall in wealth. There is a long-standing debate among researchers working in macroeconomics and finance about the value of the elasticity of intertemporal substitution (EIS). Macroeconomic models depend on an EIS below 1. In contrast, financial asset pricing models have assumed values above one to explain a feature of the data related to equity return predictability. In this paper, we estimate a value of the EIS above one, in a range between 1.5 and 3.5. Our estimation implies that the model is able to explain a variety of financial markets phenomena without having to assume that investors are unreasonably risk averse.

We do not have actual outcomes. See note in Special Reports.

The weakening of the world economy in 2008-2010 brought in an economic collapse that translated into a sharp contraction in economic activity with its associated effects on unemployment, savings and welfare. The inability of macroeconomic models to predict this collapse led to a renewed interest in what is known in financial economics as the disaster risk or rare-events hypothesis. According to this premise, the possibility of a catastrophic event (e.g. financial or economic depressions) is key to rationalize the observed co-movement between financial returns and economic variables, like output, consumption and employment. This project aims to test the ability of such hypothesis to explain the feedback between macroeconomics and finance. It does so by first assessing its applicability in developed, as well as in emerging economies. In a second stage, the project establishes the foundations to build economic models capable of rationalizing the origins and consequences of economic disasters similar to the recent financial crisis. These models will provide policy makers with tools to build early warning indicators to accurately implement economic policies when the financial conditions of households and firms deteriorate, such as in the fall of 2008. The team (at BI and Aarhus University) has already been working with disaster risk models previously. We will use this expertise to understand how these models can be extended to reconcile asset pricing puzzles across countries and over time. Similarly, we will extend the framework to understand the comovement of financial and real variables in sudden stops episodes. We will use the resources of the project to fund the costs of acquiring data, equipment and the travelling needed to gathered the group on a regular basis.