IDEAS home Printed from https://ideas.repec.org/p/qmw/qmwecw/827.html

Markov-Chain Approximations for Life-Cycle Models

Author

Listed:
  • Giulio Fella

    (Queen Mary University of London)

  • Giovanni Gallipoli

    (University of British Columbia)

  • Jutong Pan

    (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 & Jutong Pan, 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
    as

    Download full text from publisher

    File URL: https://www.qmul.ac.uk/sef/media/econ/research/workingpapers/2017/items/wp827.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Pierri, Damian Rene & Montes Rojas, Gabriel & Mira, José, 2020. "Persistent current account deficits and balance of payments crises," UC3M Working papers. Economics 34239, Universidad Carlos III de Madrid. Departamento de Economía.
    2. Damián Pierri & Gabriel Montes Rojas & Pablo Mira Lambi, 2019. "The Empirical Dimension of Overborrowing," Documentos de trabajo del Instituto Interdisciplinario de Economía Política IIEP (UBA-CONICET) 2019-45, Universidad de Buenos Aires, Facultad de Ciencias Económicas, Instituto Interdisciplinario de Economía Política IIEP (UBA-CONICET).
    3. Mariacristina De Nardi & Giulio Fella & Gonzalo Paz-Pardo, 2020. "Nonlinear Household Earnings Dynamics, Self-Insurance, and Welfare," Journal of the European Economic Association, European Economic Association, vol. 18(2), pages 890-926.
    4. Hanno Foerster, 2019. "Untying the Knot: How Child Support and Alimony Affect Couples' Decisions and Welfare," CRC TR 224 Discussion Paper Series crctr224_2019_115v2, University of Bonn and University of Mannheim, Germany.
    5. Hanno Foerster, 2019. "The Impact of Post-Marital Maintenance on Dynamic Decisions and Welfare of Couples," Boston College Working Papers in Economics 982, Boston College Department of Economics.
    6. Hong, Seungki, 2023. "MPCs in an emerging economy: Evidence from Peru," Journal of International Economics, Elsevier, vol. 140(C).
    7. Fabio Blasutto, 2024. "Cohabitation vs. Marriage: Mating Strategies by Education in The USA," Journal of the European Economic Association, European Economic Association, vol. 22(4), pages 1723-1761.
    8. Keyvan Eslami & Tom Phelan, 2023. "The Art of Temporal Approximation An Investigation into Numerical Solutions to Discrete and Continuous-Time Problems in Economics," Working Papers 23-10, Federal Reserve Bank of Cleveland.
    9. Robert Kirkby, 2025. "Discretizing earnings dynamics: implications of Gaussian-mixture shocks for life-cycle models," The Japanese Economic Review, Springer, vol. 76(2), pages 493-519, April.
    10. Keyvan Eslami & Thomas Phelan, 2025. "The Art of Temporal Approximation: An Investigation into Numerical Solutions to Discrete- and Continuous-Time Problems in Economics," Computational Economics, Springer;Society for Computational Economics, vol. 65(3), pages 1505-1547, March.
    11. Robert Kirkby, 2023. "Quantitative Macroeconomics: Lessons Learned from Fourteen Replications," Computational Economics, Springer;Society for Computational Economics, vol. 61(2), pages 875-896, February.

    More about this item

    Keywords

    ;
    ;

    JEL classification:

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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:qmw:qmwecw:827. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Nicholas Owen The email address of this maintainer does not seem to be valid anymore. Please ask Nicholas Owen to update the entry or send us the correct address (email available below). General contact details of provider: https://edirc.repec.org/data/deqmwuk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.