| ResumeNames {AER} | R Documentation |
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?
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
Examples
data("ResumeNames")
summary(ResumeNames)
prop.table(xtabs(~ ethnicity + call, data = ResumeNames), 1)