Increasing Risk: Dynamic Mean-Preserving Spreads

Abstract

We extend the celebrated Rothschild and Stiglitz (1970) definition of Mean-Preserving Spreads to a dynamic framework. We adapt the original integral conditions to transition probability densities, and give sufficient conditions for their satisfaction. We then focus on a class of nonlinear scalar diffusion processes, the super-diffusive ballistic process, and prove that it satisfies the integral conditions. We further prove that this class is unique among Brownian bridges. This class of processes can be generated by a random superposition of linear Markov processes with constant drifts. This exceptionally simple representation enables us to systematically revisit, by means of the properties of dynamic mean-preserving spreads, workhorse economic models originally based on White Gaussian Noise. A selection of four examples is presented and explicitly solved.

Daniele Rinaldo

Economist, Pianist

My research interests are development and environmental economics, currently focusing on the economic impact of endemic diseases in sub-Saharan Africa and natural resource management under regime shifts. Additionally, I work on stochastic processes and probability theory. Also a pianist.