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The Incentive Ratio in Exchange Economies

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Combinatorial Optimization and Applications (COCOA 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10043))

Abstract

The incentive ratio measures the utility gains from strategic behaviour. Without any restrictions on the setup, ratios for linear, Leontief and Cobb–Douglas exchange markets are unbounded, showing that manipulating the equilibrium is a worthwhile endeavour, even if it is computationally challenging. Such unbounded improvements can be achieved even if agents only misreport their utility functions. This provides a sharp contrast with previous results from Fisher markets. When the Cobb–Douglas setup is more restrictive, the maximum utility gain is bounded by the number of commodities. By means of an example, we show that it is possible to exceed a known upper bound for Fisher markets in exchange economies.

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Notes

  1. 1.

    Alternatively, we could assume the existence of a nonmanipulating agent who possesses at least a little bit of all commodities and who desires every commodity.

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Acknowledgments

Research funding through the Nanyang Technological University PhD research scholarship is gratefully acknowledged. I would like to thank Xiaohui Bei and Satoru Takahashi for discussions on the topic and many useful suggestions and comments on earlier versions of this manuscript. I also thank anonymous referees for helpful remarks. All remaining errors are of course my own.

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Authors and Affiliations

  1. Nanyang Technological University, Singapore, Singapore

    Ido Polak

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  1. Ido Polak
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Correspondence to Ido Polak .

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Editors and Affiliations

  1. University of Hong Kong, Hong Kong, China

    T-H. Hubert Chan

  2. City University of Hong Kong, Hong Kong, China

    Minming Li

  3. City University of Hong Kong, Hong Kong, China

    Lusheng Wang

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Polak, I. (2016). The Incentive Ratio in Exchange Economies. In: Chan, TH., Li, M., Wang, L. (eds) Combinatorial Optimization and Applications. COCOA 2016. Lecture Notes in Computer Science(), vol 10043. Springer, Cham. https://doi.org/10.1007/978-3-319-48749-6_49

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  • DOI: https://doi.org/10.1007/978-3-319-48749-6_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48748-9

  • Online ISBN: 978-3-319-48749-6

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