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Uniform boundedness of feasible per capita output streams under convex technology and non-stationary labor

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  • Maćkowiak, Piotr

Abstract

This paper shows that under classical assumptions on technological mapping and presence of an indispensable production factor there is a bound on long-term per capita production. The bound does not depend on initial state of economy. It is shown that all feasible processes converge uniformly over every bounded set of initial inputs p.c. to some set (dependent on technology).

Suggested Citation

  • Maćkowiak, Piotr, 2004. "Uniform boundedness of feasible per capita output streams under convex technology and non-stationary labor," MPRA Paper 41891, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:41891
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    File URL: https://mpra.ub.uni-muenchen.de/41891/2/Uniformly_Bounded_Trajectories.pdf
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    References listed on IDEAS

    as
    1. Levin, V. L., 1991. "Some applications of set-valued mappings in mathematical economics," Journal of Mathematical Economics, Elsevier, vol. 20(1), pages 69-87.
    2. W. A. Brock, 1970. "On Existence of Weakly Maximal Programmes in a Multi-Sector Economy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 37(2), pages 275-280.
    3. McKenzie, Lionel W., 2005. "Optimal economic growth, turnpike theorems and comparative dynamics," Handbook of Mathematical Economics, in: K. J. Arrow & M.D. Intriligator (ed.), Handbook of Mathematical Economics, edition 2, volume 3, chapter 26, pages 1281-1355, Elsevier.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    boundedness of trajectories; output path; multi-sector growth model;
    All these keywords.

    JEL classification:

    • O41 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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