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Reciprocity in Gift-Exchange-Games

Rustam Tagiew, Dmitry I. Ignatov

TL;DR

This study reanalyzes Gächter et al.'s gift-exchange-game data through a deterministic, data-driven lens to uncover regularities in reciprocal behavior beyond pure payoff maximization. It argues that many relevant variables are nominal, rendering traditional linear models inappropriate, and demonstrates notable patterns such as a 36.6% average gift rate by originators and a 69% average non-gift rate, with clear sequence-dependent effects and follower contagion. The work discusses p-hacking concerns and emphasizes transparent data practices, proposing future directions like sequential pattern mining to extract actionable behavioral rules from economic games. Overall, the paper highlights the value of deterministic regularities in experimental economics and points to data-centric methods as a complementary approach to traditional theory-driven models.

Abstract

This paper presents an analysis of data from a gift-exchange-game experiment. The experiment was described in `The Impact of Social Comparisons on Reciprocity' by Gächter et al. 2012. Since this paper uses state-of-art data science techniques, the results provide a different point of view on the problem. As already shown in relevant literature from experimental economics, human decisions deviate from rational payoff maximization. The average gift rate was $31$%. Gift rate was under no conditions zero. Further, we derive some special findings and calculate their significance.

Reciprocity in Gift-Exchange-Games

TL;DR

This study reanalyzes Gächter et al.'s gift-exchange-game data through a deterministic, data-driven lens to uncover regularities in reciprocal behavior beyond pure payoff maximization. It argues that many relevant variables are nominal, rendering traditional linear models inappropriate, and demonstrates notable patterns such as a 36.6% average gift rate by originators and a 69% average non-gift rate, with clear sequence-dependent effects and follower contagion. The work discusses p-hacking concerns and emphasizes transparent data practices, proposing future directions like sequential pattern mining to extract actionable behavioral rules from economic games. Overall, the paper highlights the value of deterministic regularities in experimental economics and points to data-centric methods as a complementary approach to traditional theory-driven models.

Abstract

This paper presents an analysis of data from a gift-exchange-game experiment. The experiment was described in `The Impact of Social Comparisons on Reciprocity' by Gächter et al. 2012. Since this paper uses state-of-art data science techniques, the results provide a different point of view on the problem. As already shown in relevant literature from experimental economics, human decisions deviate from rational payoff maximization. The average gift rate was %. Gift rate was under no conditions zero. Further, we derive some special findings and calculate their significance.

Paper Structure

This paper contains 10 sections, 2 figures, 5 tables.

Table of Contents

  1. Introduction
  2. Related Work
  3. Gift-Exchange-Game
  4. Dataset
  5. Assumption of determinism
  6. Nominal, Ordinal or Numeric
  7. Results
  8. On p-hacking
  9. Future work
  10. Conclusion

Figures (2)

  • Figure 1: Experimental non-zero-sum 2-players GEG in extensive form. (Originator's payoff, Follower's payoff) -- payoffs are in £. Payoff maximizing equilibrium is marked by dashed lines.
  • Figure 2: Choice of the second follower -- absolute statistics depending on other players' decisions encoded on x-axis as: other follower's received, own received and other follower's given. N is £0 and Y £1.6.