Markov-Chain Approximations for Life-Cycle Models

B-Tier
Journal: Review of Economic Dynamics
Year: 2019
Volume: 34
Pages: 183-201

Score contribution per author:

0.670 = (α=2.01 / 3 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

Non-stationary income processes are standard in quantitative life-cycle models, prompted by the observation that within-cohort income inequality increases with age. This paper generalizes Tauchen (1986), Adda and Cooper (2003), and Rouwenhorst's (1995) discretization methods to non-stationary AR(1) processes. We evaluate the performance of these methods in the context of a canonical life-cycle, income-fluctuation problem with a non-stationary income process. We also examine the case in which innovations to the persistent component of earnings are modeled as draws from a mixture of Normal distributions. We find that the generalized Rouwenhorst method performs consistently better than the others even with a relatively small number of states. (Copyright: Elsevier)

Technical Details

RePEc Handle
repec:red:issued:17-149
Journal Field
Macro
Author Count
3
Added to Database
2026-01-25