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Seeking Ergodicity in Dynamic Economies

Author

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  • Takashi Kamihigashi

    (Research Institute for Economics & Business Administration (RIEB), Kobe University, Japan)

  • John Stachurski

    (Research School of Economics, Australian National University, Australia)

Abstract

In estimation and calibration studies the convergence of time series sample averages plays a central role. At the same time, a significant number of economic models do not satisfy the classical ergodicity conditions. Motivated by existing work on asymptotics of stochastic economic models, we develop a new set of results on limits of sample moments and other sample averages using an ordertheoretic approach. Our results include a condition that is necessary and sufficient for convergence over a broad class of moment functions. We discuss implications, sufficient conditions and a range of economic applications.

Suggested Citation

  • Takashi Kamihigashi & John Stachurski, 2014. "Seeking Ergodicity in Dynamic Economies," Discussion Paper Series DP2014-38, Research Institute for Economics & Business Administration, Kobe University.
    • Handle: RePEc:kob:dpaper:dp2014-38
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    References listed on IDEAS

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    3. Kenichiro McAlinn & Kosaku Takanashi, 2021. "Convergence of Computed Dynamic Models with Unbounded Shock," Papers 2103.06483, arXiv.org.
    4. Bäuerle, Nicole & Jaśkiewicz, Anna, 2018. "Stochastic optimal growth model with risk sensitive preferences," Journal of Economic Theory, Elsevier, vol. 173(C), pages 181-200.
    5. Robert Kirkby, 2016. "Value Function Iteration Toolkit: In Matlab, on the GPU," EcoMod2016 9122, EcoMod.

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    More about this item

    Keywords

    Ergodicity; Monotonicity; Calibration;
    All these keywords.

    JEL classification:

    • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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