The Use of 'Reverse Regression' in Employment Discrimination Analysis

By White, Paul F.; Piette, Michael J. | Journal of Forensic Economics, Spring-Summer 1998 | Go to article overview
Save to active project

The Use of 'Reverse Regression' in Employment Discrimination Analysis

White, Paul F., Piette, Michael J., Journal of Forensic Economics

I. Introduction

In cases of alleged employment discrimination, economists often utilize multiple regression techniques to demonstrate the presence or absence of discrimination on the basis of race, age, gender, or some other personal characteristic protected under the law. Typically, the dependent variables in these analyses are salary, hire status, promotion status, or termination status. The independent variables are chosen because they are believed to explain in part the variation in the dependent variable. Common independent variables include race, age, gender, and measures of worker productivity, such as education, training, and level of output.(1)

In the context of alleged racial discrimination, the typical approach to salary discrimination measures the impact of race and other independent variables on employees' salaries. The key question is: "for given qualifications and productivity levels, are non-white employees paid significantly different than white employees?" The results of this direct regression approach determine whether the white and non-white salaries are the same at given levels of productivity.

The process of determining salaries assumed by the direct regression approach is straightforward: An employer evaluates the qualifications of an individual and determines salary level that most closely matches the qualification level. The employee's qualifications are regarded as fixed, and the salary level can vary across all levels in the firm.

It is possible, however, that another employment process may also be considered.(2) In this alternative process, an employer reviews a group of candidates for a particular salary level and selects the candidate who appears to have the best qualifications for that salary. In this case, the salary level is fixed, while the qualification level varies across the eligible candidates. Proponents of this viewpoint, called reverse regression argue that the technique is most applicable to analyze this employment selection process.

The question asked by the reverse regression approach is, "for given salary levels, are minority employees more or less qualified than non-minority employees?" This technique involves the use of productivity as the dependent variable with salary and protected class membership as the independent variables. It is implied that salary discrimination also exists if minority employees are more qualified than equally-paid white employees.

The purpose of this paper is to apply the concept of reverse regression to an employment discrimination context, discussing the strengths and weaknesses of the method. Using a database from a large manufacturing company, we compare and contrast the features of the direct regression and the reverse regression approaches. This paper also provides examples of court cases where the reverse regression technique was included as part of the statistical liability analysis.

Section II of this paper provides a detailed description of the reverse regression approach. Section III applies the reverse regression methods to data from a large manufacturing company, highlighting the differences from the traditional, direct regression methods. Section IV discusses the advantages and disadvantages of reverse regression from the point of view of an economist who is considering the use of reverse regression in his or her analysis. Section V presents examples where the reverse regression technique was used in court proceedings. In Section VI, the paper concludes with suggestions and ideas for future research.

II. The Concept of Reverse Regression

For comparison purposes, we begin this section with a brief description of the traditional or direct regression approach, which is followed by a discussion of the reverse regression methodology.

A. Direct Regression

In the context of alleged salary inequities with respect to employee race, the traditional multiple regression approach is based upon the question, "are non-white employees paid less than equally-qualified white employees?

The rest of this article is only available to active members of Questia

Sign up now for a free, 1-day trial and receive full access to:

  • Questia's entire collection
  • Automatic bibliography creation
  • More helpful research tools like notes, citations, and highlights
  • Ad-free environment

Already a member? Log in now.

Notes for this article

Add a new note
If you are trying to select text to create highlights or citations, remember that you must now click or tap on the first word, and then click or tap on the last word.
Loading One moment ...
Project items
Cite this article

Cited article

Citations are available only to our active members.
Sign up now to cite pages or passages in MLA, APA and Chicago citation styles.

Cited article

The Use of 'Reverse Regression' in Employment Discrimination Analysis


Text size Smaller Larger
Search within

Search within this article

Look up

Look up a word

  • Dictionary
  • Thesaurus
Please submit a word or phrase above.
Print this page

Print this page

Why can't I print more than one page at a time?

While we understand printed pages are helpful to our users, this limitation is necessary to help protect our publishers' copyrighted material and prevent its unlawful distribution. We are sorry for any inconvenience.
Full screen

matching results for page

Cited passage

Citations are available only to our active members.
Sign up now to cite pages or passages in MLA, APA and Chicago citation styles.

Cited passage

Welcome to the new Questia Reader

The Questia Reader has been updated to provide you with an even better online reading experience.  It is now 100% Responsive, which means you can read our books and articles on any sized device you wish.  All of your favorite tools like notes, highlights, and citations are still here, but the way you select text has been updated to be easier to use, especially on touchscreen devices.  Here's how:

1. Click or tap the first word you want to select.
2. Click or tap the last word you want to select.

OK, got it!

Thanks for trying Questia!

Please continue trying out our research tools, but please note, full functionality is available only to our active members.

Your work will be lost once you leave this Web page.

For full access in an ad-free environment, sign up now for a FREE, 1-day trial.

Already a member? Log in now.

Are you sure you want to delete this highlight?