Overview

A recent literature within quantitative macroeconomics has advocated the use of continuous-time methods for dynamic programming problems. In this workshop, we explore the relative merits of continuous-time and discrete-time methods within the context of stationary and nonstationary income fluctuation problems. We will start with a standard discrete-time income-fluctuation problem, a la Bewley-Aiyagari-Huggett, and discuss the numerical bottlenecks that made dealing with such problems traditionally computationally intensive. We want to see, in line with the anecdotal evidence, whether moving to a continuous-time framework truly alleviates these numerical bottle necks. More importantly, if so, what in the nature of a continuous-time process makes the continuous-time setting advantageous? Can we conclude that the continuous-time framework is always superior to a corresponding discrete-time one, when the only concern is computational intensity?