Abstract
Online labor markets such as Amazon Mechanical Turk (MTurk) off er an unprecedented opportunity to run economic game experiments quickly and inexpensively. Using Mturk, we recruited 756 subjects and examined their behavior in four canonical economic games, with two payoff conditions each: a stakes condition, in which subjects' earnings were based on the outcome of the game (maximum earnings of $1); and a no-stakes condition, in which subjects' earnings are una ffected by the outcome of the game. Our results demonstrate that economic game experiments run on MTurk are comparable to those run in laboratory settings, even when using very low stakes.
Highlights
Online labor markets such as Amazon Mechanical Turk (MTurk) are internet marketplaces in which people can complete short tasks in exchange for small amounts of money
We directly examine the effect of such stakes by comparing un-incentivized play with play involving typical MTurk sized stakes in four canonical economic games - the dictator game, ultimatum game, trust game and public goods game
Considering the increase of stake size, Kocher, Martinsson and Visser [18] found no significant difference in subjects’ contributions in the public goods game when going from low to high stakes, and Johansson-Stenman, Mahmud and Martinsson [19] found that in the trust game, the amount sent by investors decreased when using very high stakes but the fraction returned by trustees was not affected by the changes in stakes
Summary
Online labor markets such as Amazon Mechanical Turk (MTurk) are internet marketplaces in which people can complete short tasks (typically 5 minutes or less) in exchange for small amounts of money (typically $1 or less). We directly examine the effect of such stakes by comparing un-incentivized play with play involving typical MTurk sized stakes (up to $1) in four canonical economic games - the dictator game, ultimatum game, trust game and public goods game.
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