August 4, 2022, Paper: "When solving discrete-time consumption models with present-biased time preferences, backwards induction generates equilibria that are non-robust in the sense that policy functions are often sensitive to parameter choices, including the modeler’s choice of the time-step. The current paper identifies a range of “sweet-spot” time-steps that (i) contains the psychologically relevant presentbias horizons, and, (ii) generates numerically indistinguishable (i.e., robust) policy functions. This sweet spot includes both a computationally feasible range of discrete-time cases and the limiting continuous-time case (Harris and Laibson, 2013). Accordingly, researchers modeling present bias in buffer stock models can choose either discrete-time cases calibrated to be in the sweet spot or the analytically tractable continuous-time case; these approaches yield essentially identical policy functions. "
HKS Faculty Author - David Laibson