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Learning Language: An Experiment

Author

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  • Daniel Houser

    (Interdisciplinary Center for Economic Science and Department of Economics, George Mason University)

  • Yang Yang

    (Lingnan College, Sun Yat-sen University)

Abstract

We develop a method for random assignment of language to participants in a controlled laboratory experiment, and use this to test the hypothesis that languages are learned more quickly when they can be identified with fewer number of observations. While the theory based on this hypothesis has generated substantial attention since being advanced by Blume (2005), evidence on its empirical validity has been elusive. Here we develop a novel extension of coordination games within which languages emerge endogenously. We show, first, that one can control features of an emergent language by varying the game’s incentives. This enables us to compare speed of learning across participants randomly assigned to different languages. Our data provide cogent evidence supporting the above hypothesis and Blume’s (2005) theory: Languages with compositional structures can be identified with fewer observations and are learned more quickly, and in this sense are efficient. Despite this, we find inefficient languages to sometimes emerge when they can be expressed using simple rules.

Suggested Citation

  • Daniel Houser & Yang Yang, 2020. "Learning Language: An Experiment," Working Papers 1079, George Mason University, Interdisciplinary Center for Economic Science.
  • Handle: RePEc:gms:wpaper:1079
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    testing the efficiency theory of language; random assignment of language; laboratory experiment;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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