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?
- 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 inidacting 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).
http://wps.aw.com/aw_stock_ie_2/
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)
[Package
AER version 1.1-2
Index]