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Markov-Chain Approximations for Life-Cycle Models

Author

Listed:
  • Giulio Fella

    (Queen Mary University of London)

  • Giovanni Gallipoli

    (University of British Columbia)

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) 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.

Suggested Citation

  • Giulio Fella & Giovanni Gallipoli, 2017. "Markov-Chain Approximations for Life-Cycle Models," Working Papers 827, Queen Mary University of London, School of Economics and Finance.
  • Handle: RePEc:qmw:qmwecw:827
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    File URL: http://www.econ.qmul.ac.uk/media/econ/research/workingpapers/2017/items/wp827.pdf
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    Cited by:

    1. Mariacristina De Nardi & Giulio Fella, 2018. "Nonlinear household earnings dynamics, self-insurance, and welfare," Working Papers 860, Queen Mary University of London, School of Economics and Finance.

    More about this item

    Keywords

    Numerical methods; finite state approximations;

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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