Abstract
Social discounting is when resource allocation decreases as social distance increases. Studies fitting different quantitative models to social discounting data have shown that a q-exponential function based on Tsallis' statistics best fits loss data, whereas a hyperbolic power function best fits gain data. However, a social discounting sign effect, where losses are discounted less than equivalent gains, has not been consistently found. This study fit four different quantitative social discounting models to gain and loss data for 40 United States (US) participants. We compared quantitative model fits to previous studies collected with Japanese and German participants to determine if (1) different quantitative social discounting models best fit loss and gain data, (2) US participants discounted less gains than Japanese participants, but not losses, and (3) US participants showed the sign effect. Results showed that the q-exponential function and the hyperbolic power function best fit median loss and gain data, respectively. There were no significant absolute differences between cultures for gains or losses, and US participants showed a robust sign effect. While most results for US participants were consistent with previous data, future cross-cultural social discounting studies are needed that manipulate sign as well as reward magnitude to determine best quantitative model fits. Social discounting results are also discussed in relation to their application to important health behaviors such as smoking and obesity.
Highlights
Social discounting is allocating a reward across a social distance
This study was approved by the Institutional Review Board (IRB) at University of Texas at San Antonio (UTSA), and all participants were informed of their rights as participants prior to starting the study
We examined the fit of the four functions for gains and losses for group data: the exponential function, hyperbolic function, q-exponential function, and hyperbolic power function
Summary
Social discounting is allocating a reward across a social distance. The results of early social discounting studies were similar to delay discounting, in that a hyperbolic function accounted for a significant amount of the obtained data (1). V 1 + kN where v is the discounted value of the reward, V is the undiscounted value of the reward, N is the measure of social distance, and k is a constant measuring the degree of discounting. Larger k values indicate more discounting as a function of increasing social distance. Cross-Cultural Comparison of Social Discounting value decreases quickly at smaller delays or social distances, decreases less quickly as delays and/or social distances increase. Like previous delay discounting experiments, Jones and Rachlin (1) showed that the hyperbolic function fit their obtained social discounting data better than an exponential function:
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