Markov-chain approximations for life-cycle models - Giulio Fella; Giovanni Gallipoli; Jutong Pan (Queen Mary University of London, School of Economics and Finance, 2017)
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) and Rouwenhorst's (1995) discretization methods to non-stationary AR(1) processes. We evaluate the performance of both methods in the context of a canonical finite-horizon, income-uctuation problem with a non-stationary income process. We find that the generalized Rouwenhorst's method performs extremely well even with a relatively small number of states.
Keywords: C63; 330; Numerical methods; finite state approximations