1 / 10

Wayne State University 1993 Presented by Mahetem Gessese

An Ordered Probit Model for Estimating Racial Discrimination through Fair Housing Audits. CANOPY ROYCHOUDHURY and ALLEN C. GOODMAN. Wayne State University 1993 Presented by Mahetem Gessese. Introduction Two persons (auditors) with matched characteristics such as age, sex, and income

umeko
Download Presentation

Wayne State University 1993 Presented by Mahetem Gessese

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. An Ordered Probit Model for Estimating Racial Discrimination through Fair Housing Audits.CANOPY ROYCHOUDHURY and ALLEN C. GOODMAN Wayne State University 1993 Presented by Mahetem Gessese

  2. Introduction Two persons (auditors) with matched characteristics such as age, sex, and income Equally eligible for the housing unitDirect methods of measuring of discrimination Except one is black and one is white. The paper examines the severity of differential treatment The audit was done in metropolitan Detroit.

  3. Auditing technique, average and marginal level of discrimination • John Yinger (1986) • Tai = a + bRi +eai • Where a, is the audit i, the individual auditor, T is the treatment variable, R is binary variable for minority status and e, is the random error. • Yinger argues that the OLS estimator b for beta is unbiased • However the standard error of b is biased • He recommends a paired difference- of-means test that would remove the bias from the standard error of b • Blacks in Boston were informed 30% fewer units

  4. The model • Dj + a0 + aj +Wj + sumBij + sumvik[CiCk] +gYt + eij • i=1,2,….k • j=1,1..10 • Y* = Bx +e

  5. Existing theories of Discrimination1) The agent prejudice 2) The customer prejudice 3) The perceived preference4) The rip-off hypothesis

  6. Data569 observations317 collected randomly252 complaints-driven

  7. Regression results • Dj + a0 + aj +Wj + sumBij + sumvik[CiCk] +gYt + eij • plim(^j) + j + 1(r2/r2w)/(1-j)

  8. Conclusion

  9. Conclusion • Widespread discriminatory 1980 –1990 • Marginal discrimination higher than average discrimination

More Related