The Impact of Age on Employment Tenure: Results from an Employment Discrimination Case

By Rosenbaum, David I. | Journal of Forensic Economics, Fall 2000 | Go to article overview

The Impact of Age on Employment Tenure: Results from an Employment Discrimination Case


Rosenbaum, David I., Journal of Forensic Economics


I. Introduction

In a recent Equal Employment Opportunity Commission class action suit, a company was charged with discriminating against applicants age 40 and over. During the first phase of the trial the company was found guilty of age discrimination. The second phase of the trial involved determining damages to be awarded to a class of approximately 152 members age 40 or over. Part of the damage calculation required estimating the amount of time members of the class would have been employed, absent the discrimination.

The employer in this case argued that there was a link between age and job tenure, and that if older workers had been hired, the company's experience suggests that they would not have been employed as long as the pool of current younger workers. Therefore, in calculating damages, it is important to examine the tenure/age relationship.

Information about current and previous employees is used to predict the relationship between age and tenure. For previous employees, company records indicate the date of hire and the date of termination. For those employees tenure is calculated as the number of weeks from hire to termination. For current employees, however, the calculation is not as straightforward. The date of hire is known. But, since each is employed at the time of sampling, termination has to occur at some unknown time in the future. Therefore, each current employee's true job tenure is underestimated, starting at the date of hire and ending at the date of sampling. This is a classic censoring problem.

One way to address the censoring problem may be to remove the censored observations from the sample. This would leave a subsample of just uncensored observations, each with known job tenure. However, if the censored observations come from a different population than the uncensored observations, using only the uncensored observations for statistical analysis will lead to biased predictions. This means that a statistical procedure will have to account for censoring. Fortunately, a procedure exists to estimate job tenures when censoring is an issue. This procedure is called duration modeling.

A duration model is developed that accounts for censored data. The model allows for specifying tenure as a function of age. The model is estimated for a sample of 170 current and previous employees. The results indicate that tenure is decreasing in age. Someone starting employment at age 24, for example, would have an expected job tenure of 166 weeks. Someone starting employment at age 40 would have an expected tenure of 129 weeks.

The next section of this paper describes duration modeling. This is a statistical technique that can be used to estimate tenure as a function of age when censoring occurs. Section III describes the data related to this particular case. Results of the estimation are shown in section IV. These results are compared to results generated either by omitting censored observations or by using all observations but not accounting for censoring. This is followed by a conclusion.

II. Duration Estimation with a Censored Sample

Duration models can be used to estimate tenure when there is a censoring problem. The simplest form of the duration model makes tenure solely a function of time. Let T represent someone's tenure or duration in a job. Some employees will have a relatively short duration in a job. Others may have a relatively long duration in a job. Therefore, the duration or tenure variable, T, has some distribution associated with it. Let f(t) be the probability distribution associated with T.

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII].

This is just the probability that a particular individual's duration in a job is less than t weeks. Conversely, the probability that someone survives at least t weeks in a job is S(t) = 1 - F(t). Not surprisingly, this is called a survival function. Putting the probability function and the survival function together, it is possible to estimate the probability that someone who has already lasted t weeks in a job, leaves before the next week is out. …

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

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.
One moment ...
Default project is now your active project.
Project items

Items saved from this article

This article has been saved
Highlights (0)
Some of your highlights are legacy items.

Highlights saved before July 30, 2012 will not be displayed on their respective source pages.

You can easily re-create the highlights by opening the book page or article, selecting the text, and clicking “Highlight.”

Citations (0)
Some of your citations are legacy items.

Any citation created before July 30, 2012 will labeled as a “Cited page.” New citations will be saved as cited passages, pages or articles.

We also added the ability to view new citations from your projects or the book or article where you created them.

Notes (0)
Bookmarks (0)

You have no saved items from this article

Project items include:
  • Saved book/article
  • Highlights
  • Quotes/citations
  • Notes
  • Bookmarks
Notes
Cite this article

Cited article

Style
Citations are available only to our active members.
Buy instant access to cite pages or passages in MLA, APA and Chicago citation styles.

(Einhorn, 1992, p. 25)

(Einhorn 25)

1. Lois J. Einhorn, Abraham Lincoln, the Orator: Penetrating the Lincoln Legend (Westport, CT: Greenwood Press, 1992), 25, http://www.questia.com/read/27419298.

Cited article

The Impact of Age on Employment Tenure: Results from an Employment Discrimination Case
Settings

Settings

Typeface
Text size Smaller Larger Reset View mode
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?

Help
Full screen

matching results for page

    Questia reader help

    How to highlight and cite specific passages

    1. Click or tap the first word you want to select.
    2. Click or tap the last word you want to select, and you’ll see everything in between get selected.
    3. You’ll then get a menu of options like creating a highlight or a citation from that passage of text.

    OK, got it!

    Cited passage

    Style
    Citations are available only to our active members.
    Buy instant access to cite pages or passages in MLA, APA and Chicago citation styles.

    "Portraying himself as an honest, ordinary person helped Lincoln identify with his audiences." (Einhorn, 1992, p. 25).

    "Portraying himself as an honest, ordinary person helped Lincoln identify with his audiences." (Einhorn 25)

    "Portraying himself as an honest, ordinary person helped Lincoln identify with his audiences."1

    1. Lois J. Einhorn, Abraham Lincoln, the Orator: Penetrating the Lincoln Legend (Westport, CT: Greenwood Press, 1992), 25, http://www.questia.com/read/27419298.

    Cited passage

    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.

    Buy instant access to save your work.

    Already a member? Log in now.

    Author Advanced search

    Oops!

    An unknown error has occurred. Please click the button below to reload the page. If the problem persists, please try again in a little while.