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Be a Good Samaritan to a Good Samaritan: Field Evidence of Interdependent Other-Regarding Preferences in China

Author

Listed:
  • Chang, Simon

    (University of Western Australia)

  • Dee, Thomas S.

    (Stanford University)

  • Tse, Chun-Wing

    (Central University of Finance and Economics)

  • Yu, Li

    (Central University of Finance and Economics)

Abstract

We conducted large-scale lost letter experiments in Beijing, a megacity with more than 21 million residents, to test if the observed altruistic attribute of the letter recipient would induce more passersby to return the lost letters. The treatment letters were addressed to a nationally renowned charitable organization in China, while the control letters were intended to an invented individual. A total of 832 ready-to-be-posted letters were distributed in 208 communities across eight districts in the city. The overall return rate was only about 13%. Yet, the return rate of the treatment letters (17%) was nearly twice as high as that of the control letters (9%). The finding adds large-scale field experiment evidence in support of the interdependent other-regarding preferences theory. In addition, we also found that the lost letters were more likely to be returned if they were dropped in communities with a relatively higher income or a postal box located closer.

Suggested Citation

  • Chang, Simon & Dee, Thomas S. & Tse, Chun-Wing & Yu, Li, 2015. "Be a Good Samaritan to a Good Samaritan: Field Evidence of Interdependent Other-Regarding Preferences in China," IZA Discussion Papers 9319, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp9319
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    lost letter technique; other-regarding preferences; China; altruism;
    All these keywords.

    JEL classification:

    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles

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