Inaccurate Statistical Discrimination: An Identification Problem
研究不准确信念作为歧视来源，通过理论和实验表明忽视不准确信念会导致歧视来源的误判，并提出了三种识别方法。
Abstract We study inaccurate beliefs as a source of discrimination. Economists typically characterize discrimination as stemming from a taste-based (preference) or accurate statistical (belief-based) source. Although individuals may have inaccurate beliefs about how relevant characteristics (e.g., productivity, signals) are correlated with group identity, fewer than 7% of empirical discrimination papers in economics consider the possibility of such inaccurate statistical discrimination. Using theory and a labor market experiment, we show that failing to account for inaccurate beliefs leads to a misclassification of source. We outline three methods to identify source: varying observed signals, belief elicitation, and an intervention to target inaccurate beliefs.