ResumeNames: Are Emily and Greg More Employable Than Lakisha and Jamal?

In AER: Applied Econometrics with R

Are Emily and Greg More Employable Than Lakisha and Jamal?

Description

Cross-section data about resume, call-back and employer information for 4,870 fictitious resumes.

Usage

data("ResumeNames")

Format

A data frame containing 4,870 observations on 27 variables.

name

factor indicating applicant's first name.

gender

factor indicating gender.

ethnicity

factor indicating ethnicity (i.e., Caucasian-sounding vs. African-American sounding first name).

quality

factor indicating quality of resume.

call

factor. Was the applicant called back?

city

factor indicating city: Boston or Chicago.

jobs

number of jobs listed on resume.

experience

number of years of work experience on the resume.

honors

factor. Did the resume mention some honors?

volunteer

factor. Did the resume mention some volunteering experience?

military

factor. Does the applicant have military experience?

holes

factor. Does the resume have some employment holes?

school

factor. Does the resume mention some work experience while at school?

email

factor. Was the e-mail address on the applicant's resume?

computer

factor. Does the resume mention some computer skills?

special

factor. Does the resume mention some special skills?

college

factor. Does the applicant have a college degree or more?

minimum

factor indicating minimum experience requirement of the employer.

equal

factor. Is the employer EOE (equal opportunity employment)?

wanted

factor indicating type of position wanted by employer.

requirements

factor. Does the ad mention some requirement for the job?

reqexp

factor. Does the ad mention some experience requirement?

reqcomm

factor. Does the ad mention some communication skills requirement?

reqeduc

factor. Does the ad mention some educational requirement?

reqcomp

factor. Does the ad mention some computer skills requirement?

reqorg

factor. Does the ad mention some organizational skills requirement?

industry

factor indicating type of employer industry.

Details

Cross-section data about resume, call-back and employer information for 4,870 fictitious resumes sent in response to employment advertisements in Chicago and Boston in 2001, in a randomized controlled experiment conducted by Bertrand and Mullainathan (2004). The resumes contained information concerning the ethnicity of the applicant. Because ethnicity is not typically included on a resume, resumes were differentiated on the basis of so-called “Caucasian sounding names” (such as Emily Walsh or Gregory Baker) and “African American sounding names” (such as Lakisha Washington or Jamal Jones). A large collection of fictitious resumes were created and the pre-supposed ethnicity (based on the sound of the name) was randomly assigned to each resume. These resumes were sent to prospective employers to see which resumes generated a phone call from the prospective employer.

Source

Online complements to Stock and Watson (2007).

References

Bertrand, M. and Mullainathan, S. (2004). Are Emily and Greg More Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination. American Economic Review, 94, 991–1013.

Stock, J.H. and Watson, M.W. (2007). Introduction to Econometrics, 2nd ed. Boston: Addison Wesley.

See Also

StockWatson2007

Examples

data("ResumeNames")
summary(ResumeNames)
prop.table(xtabs(~ ethnicity + call, data = ResumeNames), 1)

AER documentation built on Sept. 28, 2024, 9:07 a.m.