Detecting Discrimination in Audit and Correspondence Studies
针对通信研究中因不可观测因素方差差异导致的歧视估计偏误，提出一种利用申请人特征变异来恢复无偏估计的方法，并用蒙特卡洛方法验证。
Audit studies testing for discrimination have been criticized because applicants from different groups may not appear identical to employers. Correspondence studies address this criticism by using fictitious paper applicants whose qualifications can be made identical across groups. However, Heckman and Siegelman (1993) show that group differences in the variance of unobservable determinants of productivity still can generate spurious evidence of discrimination in either direction. This paper shows how to recover an unbiased estimate of discrimination when the correspondence study includes variation in applicant characteristics that affect hiring. The method is applied to actual data and assessed using Monte Carlo methods.