Markov-Chain Approximations for Life-Cycle Models


Non-stationary income processes are standard in quantitative life-cycle models. Their approximation is key for numerical implementations. We develop methods to apply standard discretization algorithms within non-stationary life-cycle settings and assess their relative performance. In one extension we examine income processes in which shocks to earnings are modeled as draws from a mixture of Normal distributions and describe simple and tractable approaches to numerically describe non-Normal earnings distributions.

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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’s method performs consistently better than the others even with a relatively small number of states.

Citation

@article{fgp2019approximations,
  title={Markov-Chain Approximations for Life-Cycle Models},
  author={Fella, Giulio and Gallipoli, Giovanni and Pan, Jutong},
  journal={Review of Economic Dynamics},
  year={2019},
  volume = {34},
  pages = {183-201}
}

Author: gallipol

Giovanni Gallipoli is a professor at UBC in Vancouver. Giovanni's research focuses on the origins and consequences of economic inequality with a focus on how heterogeneity shapes individual behaviors and aggregate economic outcomes. Giovanni has worked on a variety of topics, including the equilibrium effects of policies that promote skill formation; the link between skill heterogeneity and a country's comparative advantage; the influence of families on long-term outcomes such as labor supply and consumption; intergenerational mobility and the linkages between parental heterogeneity and inequality; and how firm-level differences contribute to variation in workers’ skill returns. Giovanni is a recipient of the Killam Research Award, the FEEM Award, and the Young Economist Award of the European Economic Association. He is a CEPR research fellow as well as a former Fulbright Scholar and Weatherhall fellow. He serves as a member of the external board of overseers of the Panel Study of Income Dynamics (PSID) and as an associate editor of the Journal of Political Economy. Giovanni is an alumnus of the Sant'Anna School of Advanced Studies and the University of Pisa in Italy. He received his Ph.D. in Economics from University College London in the UK.