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Long-run technology choice with endogenous local capacity

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  • Fei Shi

Abstract

We develop a two-stage, two-location model to investigate long-run technology choice with endogenous capacity constraints. Rational managers determine the maximum capacities (and mobility constraints). Then, boundedly rational agents play a coordination game with the possibility to migrate. We consider two alternative strategy sets and two different objective functions for the managers and show that they affect the long-run technology choice in a non-trivial way. If the managers only care about efficiency in their respective locations, either coexistence of conventions or global coordination on the risk-dominant equilibrium will be selected, depending on the (effective) capacities of both locations. If they are concerned with scale and can choose mobility constraints, global coordination on the risk-dominant equilibrium without mobility will be selected in the long run. We then change the basic interaction to a $$n\times n$$ n × n pure coordination game where mis-coordination results in zero payoff, and show that, regardless of the constraint choices, all the agents will coordinate on the most efficient equilibrium. Copyright Springer-Verlag Berlin Heidelberg 2015

Suggested Citation

  • Fei Shi, 2015. "Long-run technology choice with endogenous local capacity," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 59(2), pages 377-399, June.
  • Handle: RePEc:spr:joecth:v:59:y:2015:i:2:p:377-399
    DOI: 10.1007/s00199-014-0838-7
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    Cited by:

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    3. Tsakas, Nikolas, 2017. "Diffusion by imitation: The importance of targeting agents," Journal of Economic Behavior & Organization, Elsevier, vol. 139(C), pages 118-151.
    4. Carlos Alós-Ferrer & Georg Kirchsteiger, 2015. "Learning and market clearing: theory and experiments," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 60(2), pages 203-241, October.
    5. Alós-Ferrer, Carlos & Buckenmaier, Johannes, 2017. "Trader matching and the selection of market institutions," Journal of Mathematical Economics, Elsevier, vol. 69(C), pages 118-127.
    6. Agrawal, Asha Weinsten & Granger-Bevan, Stephen & Newmark, Gregory L. & Nixon, Hilary, 2017. "Comparing data quality and cost from three modes of on-board transit surveys," Transport Policy, Elsevier, vol. 54(C), pages 70-79.
    7. Pin, Paolo & Weidenholzer, Elke & Weidenholzer, Simon, 2017. "Constrained mobility and the evolution of efficient outcomes," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 165-175.

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    More about this item

    Keywords

    Location models; Long-run technology choice; Stochastic learning; C72; C73; D83;
    All these keywords.

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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