UCLA

AbstractEconomics games such as the Dictator and Public Goods Games have been widely used to measure ethnic bias in political science and economics. Yet these tools may fail to measure bias as intended because they are vulnerable to self-presentational concerns and/or fail to capture bias rooted in more automatic associative and affective reactions. We examine a set of misattribution-based approaches, adapted from social psychology, that may sidestep these concerns. Participants in Nairobi, Kenya completed a series of common economics games alongside versions of these misattribution tasks adapted for this setting, each designed to detect bias toward noncoethnics relative to coethnics. Several of the misattribution tasks show clear evidence of (expected) bias, arguably reflecting differences in positive/negative affect and heightened threat perception toward noncoethnics. The Dictator and Public Goods Games, by contrast, are unable to detect any bias in behavior toward noncoethnics versus coethnics. We conclude that researchers of ethnic and other biases may benefit from including misattribution-based procedures in their tool kits to widen the set of biases to which their investigations are sensitive.