Telles E E, Lim N
Ford Foundation, Rio de Janeiro Office, New York, NY 10017, USA.
Demography. 1998 Nov;35(4):465-74.
Previous studies of racial inequality have relied on official statistics that presumably use self-classification of race. Using novel data from a 1995 national survey in Brazil, we find that the estimates of racial income inequality based on self-classification are lower than those based on interviewer classification. After human capital and labor market controls, whites earn 26% more than browns with interviewer classification but earn only 17% more than browns with self-classification. Black-brown differences hardly change: Blacks earn 13% and 12% less than browns with interviewer classification and self-classification, respectively. We contend that interviewer classification of race is more appropriate because analysts of racial inequality are interested in the effects of racial discrimination, which depends on how others classify one's race.
以往关于种族不平等的研究依赖于官方统计数据,这些数据大概使用的是种族的自我分类。利用巴西1995年全国调查的新数据,我们发现基于自我分类的种族收入不平等估计低于基于访谈者分类的估计。在控制了人力资本和劳动力市场因素后,按照访谈者分类,白人比棕色人种的收入高26%,但按照自我分类,白人只比棕色人种多挣17%。黑人和棕色人种之间的差异变化不大:按照访谈者分类,黑人比棕色人种少挣13%,按照自我分类则少挣12%。我们认为访谈者对种族的分类更合适,因为种族不平等的分析者感兴趣的是种族歧视的影响,而这取决于他人如何对一个人的种族进行分类。